Please help me out with this assignment, case study 3. You can use the articles and graphs on “case study 3“ file to finish this assignment. Thanks.

Stuck with a difficult assignment? No time to get your paper done? Feeling confused? If you’re looking for reliable and timely help for assignments, you’ve come to the right place. We promise 100% original, plagiarism-free papers custom-written for you. Yes, we write every assignment from scratch and it’s solely custom-made for you.


Order a Similar Paper Order a Different Paper

Please help me out with this assignment, case study 3. You can use the articles and graphs on “case study 3“ file  to finish this assignment. Thanks.

Please help me out with this assignment, case study 3. You can use the articles and graphs on “case study 3“ file to finish this assignment. Thanks.
Dengue in a changing climate Kristie L. Ebi a,1, n, Joshua Nealon b,2 aDepartments of Global Health and Environmental and Occupational Health Sciences, University of Washington, WA 98015, USAbSanofiPasteur Asia Pacific Epidemiology, 189767, Singapore article info Article history: Received 29 March 2016 Received in revised form 10 June 2016 Accepted 18 July 2016 Available online 29 July 2016 Keywords: Climate change Dengue Aedes aegypti Aedes albopictus Vector control Dengue vaccine abstract Dengue is the world’s most important arboviral disease in terms of number of people affected. Over the past 50 years, incidence increased 30-fold: there were approximately 390 million infections in 2010. Globalization, trade, travel, demographic trends, and warming temperatures are associated with the recent spread of the primary vectorsAedes aegyptiandAedes albopictusand of dengue. Overall, models project that new geographic areas along the fringe of current geographic ranges forAedeswill become environmentally suitable for the mosquito’s lifecycle, and for dengue transmission. Many endemic countries where dengue is likely to spread further have underdeveloped health systems, increasing the substantial challenges of disease prevention and control. Control focuses on management ofAedes, al- though these efforts have typically had limited effectiveness in preventing outbreaks. New prevention and control efforts are needed to counter the potential consequences of climate change on the geo- graphic range and incidence of dengue, including novel methods of vector control and dengue vaccines. &2016 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). 1. Introduction Worldwide, dengue is the most important vector-borne viral disease that is transmitted to humans by mosquitoes. The burden of disease has increased an estimated 30-fold over the past 50 years (Global alert and response, 2015). Globalization, trade, ur- banization, travel, demographic change, inadequate domestic water supplies and warming temperatures are associated with the spread of the main vectorsAedes aegypti and Aedes albopictus (Murray et al., 2013).Ae. aegypti, originally from Africa, andAe. albopictus, from Asia, rapidly expanded their range over the past 50 years, transported among continents and spread overland by the global shipping industry, in rubber tires or other containers in which eggs had been laid. Dengue virus (DENV) also spreads ra- pidly via infected travelers (Wilder-Smith, 2012), whose numbers have increased over recent decades (Semenza et al., 2014). Climate change may lead to changes in these determinants of dengue transmission by multiple, inter-related mechanisms. The identification of factors, particularly environmental vari- ables, that can be used to forecast epidemics is important to allow sufficient time for health systems to be prepared, and will improveour understanding of how a changing climate may contribute to the geographic expansion of mosquitoes and disease into new areas. Here, we synthesize recent literature, offering insights into the projected future distributions ofAedesvectors and dengue transmission under climate change. 2. Worldwide burden and distribution of dengue fever Dengue disease (varying in clinical manifestations from acute febrile illness, self-limiting episodes [dengue fever, DF] to severe hemorrhagic manifestations [dengue hemorrhagic fever, DHF] and death) is caused by any one of four closely related dengue viral serotypes (DENV- 1, DENV-2, DENV-3, and DENV-4) of the genus Flavivirus, belonging to the familyFlaviviridae. The worldwide distribution and incidence of dengue infections and cases are difficult to accurately establish because only approximately 20% of those infected with dengue virus exhibit apparent clinical symp- toms. Disease occurs across a spectrum, and many patients with milder manifestations never seek health care. Additionally, of those patients who enter healthcare facilities, non-specific symp- toms may be confused with other diseases or fail to satisfy re- porting criteria: national passive surveillance systems are not de- signed to capture all symptomatic cases. Consistent burden esti- mates are elusive; from 2010 to 2013, the World Health Organi- zation (WHO) reported an increase from 2.4 million to over 3 million reported cases from the three affected regions (Americas, South-East Asia, and Western Pacific). Accordingly, their 2012 Global Strategy estimated a total of 50–100 million infections per Contents lists available atScienceDirect journal homepage:www.elsevier.com/locate/envres Environmental Research http://dx.doi.org/10.1016/j.envres.2016.07.026 0013-9351/&2016 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). nCorresponding author. E-mail addresses:[email protected](K.L. Ebi), [email protected]fipasteur.com(J. Nealon). 1School of Public Health, University of Washington, 4225 Roosevelt Way NE #100, Seattle WA 98015, USA. 2SanofiPasteur, Asia Pacific Epidemiology, 38 Beach Road #18-11 South Beach Tower, Singapore 189767. Environmental Research 151 (2016) 115–123 year (Global alert and response, 2015;World Health Organization, 2012). These estimates were updated following a study in which the global distribution of dengue was modeled to map the risk of disease based on an exhaustive assembly of records of dengue occurrence. These data included environmental and socio- economic covariates known or hypothesized to affect transmission (Bhatt et al., 2013). The authors estimated that worldwide in 2010, there were approximately 390 million (range 284–528 million) dengue infections, 96 million (range 67–136 million) of which were clinically apparent. These infection rates were more than three times higher than those previously estimated by the WHO (Global alert and response, 2015), and included cases from 36 countries previously considered dengue-free (Brady et al., 2012). People in more than 125 countries, or over 50% of the world’s population, were identified as being at risk of infection, including 824 million individuals in urban and 763 million in peri-urban areas (Brady et al., 2012). Dengue was predicted to be ubiquitous year-round in the tropics, with the highest risk zones in the Americas and Asia. Asia bore 70% of the global burden of apparent infections, with India contributing 34% of the total. The Americas accounted for 14%, with more than half occurring in Brazil and Mexico. Africa contributed 16%, with the predicted risk unevenly distributed and more widespread than previously suggested; however, documentation of data was poorest in Africa suggesting this could be an underestimate. Overall, this analysis may over- estimate the number of dengue infections in some countries, such as in Hong Kong where, in contrast to a study estimate of 4300,000 episodes annually, very few cases occur, and under- estimate it in others; in the USA, the study predicted zero dengue transmission whereas local transmission occurs along the US- Mexico border and in Florida (Radke et al., 2012;Ramos et al., 2008). Suitable local temperature and high levels of precipitation were the variables most strongly associated with elevated dengue risk; in some locations, dengue is associated with humidity and vapor pressure (Bhatt et al., 2013;Estallo et al., 2015). Proximity to low- income urban and peri-urban centers was also associated with greater risk, particularly for those with good transport connections (Bhatt et al., 2013). Climatic changes resulting in increased tem- perature and rainfall, together with urbanization, may therefore be associated with increased dengue incidence and outbreak risk. In addition to the public health impacts, the economic burden of dengue can be substantial. Shepard et al. suggest that the eco- nomic costs of endemic dengue for individual professional healthcare systems can exceed hundreds of millions of US$ an- nually (Shepard et al., 2014). A review of 17 publications con- ducted in different geographic and health system settings reported that estimated costs for outbreaks in 2011 (in 2012 US$) ranged from US$2.8 million in the Dominican Republic to US$12 million in Vietnam (Stahl et al., 2013). Overall, the global aggregate direct (medical care and travel) and indirect (lost time and productivity) cost of dengue has been estimated as US$8.9 billion (Shepard et al., 2015). 3.Aedesmosquitoes Historically, the prevention and control of dengue depended on controlling theAedesvector mosquitoes. The primary vector,Ae. aegypti,is closely associated with humans and their dwellings. Water-holding containers in and around homes are used by the mosquitoes to complete their development, while people provide the blood meals required by female mosquitoes for egg develop- ment.Ae. aegyptipreferentially rests in dark, cool areas, such as closets, and generally bites indoors (SeeSupplementary Table S1for a comparison ofAe. aegyptiandAe. albopictus). Eggs are laid on the side of water-holding containers and hatch into larvae after rain orflooding. The larvae transform into pupae, and then adult mosquitoes, in little over a week under favorable environmental conditions. Females are predominantly infected with dengue viruses after biting a viremic human. Vertical trans- mission between generations also may occur to an extent, al- though its significance is debated (Grunnill and Boots, 2016). It takes between 5 and 33 days at 25°C, with a mean of 15 days, for viruses to multiply, mature, and migrate to the salivary glands before the mosquito can transmit the virus to another person (Chan and Johansson, 2012). The geographic range ofAedeshas varied over time. In thefirst half of the 20th century,Ae. aegyptiwas reported sporadically in Europe from the Atlantic coast (Britain, France, and Portugal) to the Black Sea, with a wider distribution than today (Aedes aegypti, 2015). The same is true for North America and Australia. The re- ductions observed since in these regions were possibly due to eradication programs, but were more likely caused by develop- mental changes including improvements in piped water, sanita- tion, and housing conditions.Ae. aegyptisubsequently re-colo- nized Madeira, Portugal (leading to a dengue outbreak in 2012 with more than 2000 cases), parts of southern Russia and Georgia, and was imported to the Netherlands (Almeida et al., 2007; Scholte et al., 2010). In the United States, dengue reappeared in the early 2000s following 75 years of absence, leading to locally ac- quired disease (Anez and Rios, 2013). This re-emergence was due to the widespread distribution ofAedes, insufficient mosquito control measures, availability of mosquito habitats in urban land- scapes, and increased frequency of DENV-infected visitors. In 2014, Japan recorded itsfirst cases of locally acquired dengue fever after 70 years of absence; 160 cases were confirmed in a Tokyo outbreak between August and October (Kutsuna et al., 2015).Ae. albopictus was the likely vector. Overall, there has been a small pole-ward shift of the mean absolute latitude ofAe. albopictusdistribution since 1960 and small equator-ward shifts of the mean absolute latitude ofAe. aegyptiand of dengue (Rogers, 2015). Kraemer et al. mapped the global distribution ofAe. aegyptiand Ae. albopictusand the geographical determinants of their ranges based on occurrence data from published literature and en- tomological surveys between 1960 and 2014 (Kraemer et al., 2015). The authors paired the database with environmental variables, including species-specific temperature suitability and land-cover variables, to predict the global distribution of each mosquito species. The model predictedAe. aegyptito exist primarily in the tropics and sub-tropics, with concentrations in northern Brazil and southeast Asia (including all of India) and low occurrence in Eur- ope and North America (Fig. 1a). It predicts that in Australia,Ae. aegyptiis largely confined to the east coast, while the distribution ofAe. albopictusextends into southern Europe, northern China, southern Brazil, northern United States, and Japan (Fig. 1b). For both species, temperature was the most important predictor of distribution, with precipitation and vegetation also providing va- luable information. Urbanization was poorly correlated (Kraemer et al., 2015). The predicted distributions ofAe. aegyptiandAe. albopictus contained most but not all of the locations where dengue disease occurs, indicating areas of further opportunity for dengue to spread. Brady et al. determined the global temperature constraints on the persistence of these two species and on their competence for DENV transmission (Brady et al., 2014). Temperature was im- portant not only in limiting the absolute geographic limits of DENV transmission, but also in supporting different levels of en- demicity. The authors concluded that when considering the full range of transmission determinants, and in contrast to its per- ceived status as a“secondary”vector,Ae. albopictushas a greater K.L. Ebi, J. Nealon / Environmental Research 151 (2016) 115–123 116 capacity for DENV transmission thanAe. aegypti, and that the wider predicted distribution of this species could allow trans- mission during optimal seasons at higher latitudes than currently observed.Ae. albopictuseggs are especially hardy, facilitating sur- vival over winter and on slow-moving transport, with subsequent colonization and survival in new geographies. The more limited evidence of this species transmitting DENV may be due to reasons including its ecology, and because mostAedessurvey methods focus on household container types in whichAe. aegyptiare more likely to be found. In addition to humans,Ae albopictushas catholic feeding habits, frequently targeting birds and other animals. This characteristic likely reduces the frequency of DENV transmission to humans and may explain why this species is considered less likely to cause dengue epidemics. 4. Control ofAedesmosquitoes It is very difficult to control or eliminateAedesmosquitoes, and after their introduction, they can become established if climaticand ecological conditions are suitable. They adapt to human en- vironments and their populations often recover from natural dis- turbances, such as drought, or human control measures. Indeed, Aedeseggs can withstand drying and survive without water for several months on the inner walls of containers on which they were laid, hatching immediately after being submerged following rainfall. This speed of development means a population could re- cover within weeks after a vector control campaign successfully eliminates all larvae, pupae, and adultAe. aegyptifrom a site (Dengue–entomology and ecology, 2015). Given these challenges and the need for sustained, community- based vector control approaches, there has been a recent focus on implementing an integrated approach, incorporating locally appro- priate packages of vector control interventions alongside improved dengue surveillance and outbreak response. A number of novel and promising vector control tools are under development that show some evidence of epidemiological impact; these remain a topic of ongoing research (Achee et al., 2015;Andersson et al., 2015). There is increasing interest in developing early warning sys- tems to predict dengue outbreaks with sufficient lead time for Fig. 1.Global maps of the probability of occurrence of a. Ae. aegypti and b. Ae. albopictus from 0 (blue) to 1 (red) at a spatial resolution of 5 km by 5 km. Source:Kraemer et al. (2015). (For interpretation of the references to color in thisfigure legend, the reader is referred to the web version of this article.) K.L. Ebi, J. Nealon / Environmental Research 151 (2016) 115–123117 implementation of public health interventions. Numerous para- meters have been used to attempt to forecast outbreaks of dengue (Racloz et al., 2012). Comparative assessment of the effectiveness of such models is difficult because of differences between ap- proaches in terms of objectives, biological factors, spatio-temporal parameters, geographical scales, and mathematical equations (Supplementary Table S2). One review highlighted the benefits of combining climatic, environmental, epidemiologic, and socio- economic factors to forecast outbreaks and thus provide lead time for prevention and control activities (Racloz et al., 2012). However, Bowman et al. found little evidence of a quantifiable association between indices of mosquito populations and dengue transmis- sion that could be reliably used for forecasting outbreaks (Bowman et al., 2014). This is reflective of a historical lack of association between dengue entomologic and epidemiologic parameters, and challenges the operational utility of predictive models in many settings (Bowman et al., 2014). 5. Factors affecting the magnitude and patterns of risks from dengue The magnitude and pattern of dengue risk depends on inter- related human, vector, environment, and virus-related factors. 5.1. Weather and climate variability Variations in weather and climate can affect theAedesmos- quitoes and DENV through multiple mechanisms (Fig. 2)(Morin et al., 2013). Temperature is an important determinant of biting rate, egg and immature mosquito development, development time of virus in the mosquito (extrinsic incubation period), and survival at all stages of the mosquito life cycle (Christophers, 1960). La- boratory studies assessing these factors indicated that the ideal temperature range for survival through all life phases ofAe. aegypti is between 20 and 30°C(Tun-Lin et al., 2000). In some environ- ments, elevated temperatures can thus increase the rate of mos- quito mortality and decrease dengue risk. However,Aedeshas adapted to human landscapes by overwintering in sewers and seeking shaded areas during daylight hours in hot environments.The time between feeding and virus detection in the salivary glands ofAe. aegyptidecreased from 9 days at 26°C and 28°Cto 5 days at 30°C for DENV-1 and DENV-4 (Rohani et al., 2009). Feeding behavior is also more frequent at higher temperatures, further affecting transmission risk. Assuming mosquitoes are in- fected with DENV when they take theirfirst blood meal, 10–39% should survive long enough to become infectious to humans, a proportion that is temperature dependent (Christophers, 1960). Diurnal temperature range is also important for dengue transmission byAe. aegypti(Lambrechts et al., 2011). Thermo- dynamic modeling predicts that at low mean temperatures (o 18°C), increases in diurnal temperature ranges led to increased DENV transmission, whereas at mean temperatures418°C, the effect was reversed. Indeed, at 26°C, mosquitoes were susceptible to infection and survived for a shorter period under larger diurnal temperature ranges (Lambrechts et al., 2011). Carrington et al. found that a small diurnal temperature range had no effect on vector competence at a high mean temperature (30°C), but a large diurnal temperature range at a low temperature (20°C) increased the proportion of infected mosquitoes that could disseminate in- fection by 60% (Carrington et al., 2013). In line with thesefindings, Liu-Helmersson et al. showed that a higher diurnal temperature range was associated with increased dengue epidemic potential in both cold-to-temperate and extremely hot climates (Liu-Hel- mersson et al., 2014). The model suggested that small increases in dengue epidemic potential occurred over the past 100 years. Since 1950, diurnal temperature range increased and magnitudes of annual temperature cycles increased by 0.4°C in temperate re- gions (Vasseur et al., 2014), which means possible impacts on dengue outbreak risk if this trend continues. These temperature-dependent relationships differ depending on theAedesspecies. Brady et al. created survival models forAe. aegyptiandAe. albopictusacross their range of viable tempera- tures, showing thatAe. albopictushas higher survival rates and thus may become a more important vector in some regions (Brady et al., 2014).Ae. aegyptican tolerate a wider range of temperatures, presumably by exploiting habitats in urban areas with favorable temperatures. Precipitation provides habitats for the aquatic stages of the mosquito life cycle and strongly influences vector distribution Fig. 2.Biophysical influences on dengue ecology showing the interactions between climate variables, vectors, and the virus. The numbers in thefigure identify relationships between variables supported by research in thefield and under controlled laboratory conditions: Habitat availability for mosquito larvae is influenced by (1) temperature through evaporation and transpiration, (2) incoming precipitation, Temperature is a major regulator of (3) mosquito development, (4) viral replication within infected mosquitoes, (5) mosquito survival, (6) the reproductive behavior of mosquitoes, Habitat availability is required for (7) survival, (8) egg-laying, Mosquito reproduction is accelerated by (9) faster mosquito development, (10) increased survival, Increased mosquito reproduction (11) enhances the likelihood of transmission by increasing the number of blood feedings, Faster viral replication (12) increases transmission by shortening the time for the virus to develop in the mosquito, Increased survival of the adult mosquito (13) increases the amount of viral replication. Source:Morin et al. (2013). K.L. Ebi, J. Nealon / Environmental Research 151 (2016) 115–123 118 (Morin et al., 2013). The effects of precipitation and evaporation on available water sources can regulate the size, population, and be- havior ofAedes. For example, in Taiwan, the risk of dengue in- creased over a period of up to 15 weeks, once the daily maximum 24-h rainfall reached450 mm but there was a temporary one- month decrease in dengue risk following extreme rainfall (Chien and Yu, 2014). In some regions, precipitation changes with La Niña and El Niño conditions, which affects mosquito distributions (Kolivras, 2010). Several studies identified climate-dengue relationships that could be used successfully for predictive modeling (Morin et al., 2013). Weather variables that predicted the intensity and timing of outbreaks included minimum, maximum, and mean temperature; relative humidity; and wind velocity. The seasonal timing of out- breaks was predicted by precipitation. The sign and strength of the relationships depended on the local weather context (Morin et al., 2013). In their review of the associations between weather and cli- mate variability and dengue incidence,Morin et al. (2013)con- cluded that changes in climate could alter the spatial and temporal dynamics of dengue ecology, potentially increasing vector ranges, lengthening the duration of vector activity, and increasing the mosquito’s infectious period. At the same time, increasing tem- peratures in currently warm locations may reduce transmission. Weather and climate influence disease ecology at many levels, with feedback and non-linear relationships creating complex dy- namics that are not easily modeled. Human factors, such as be- havior, immunity, and socioeconomic factors, contribute to the complexity. Other weather variables, such as humidity and evaporation rate, influence vector competence, biting behavior, and adult mosquito survival, but have received less attention. For example, in Thailand, ambient temperature appears to define a viable range for transmission, and humidity amplifies the potential within that range (Campbell et al., 2013). Eighty percent of severe dengue cases over the period 1983–2001 occurred when the temperature was 27–29.5°C and mean humidity was475%. Given that warmer temperatures can bring higher humidity, understanding these in- teractions is important for early warning systems and for pro- jecting how a changing climate could alter the future burden of dengue. A changing climate may also affect the geographic range and incidence of dengue through effects on human and natural sys- tems, such as water storage, land use, and irrigation. Population movement can affect vector ecology and human exposure to in- fection. Further, natural climate variability and longer-term cli- mate change can interact to affect dengue transmission. Forexample, temperature increases associated with El Niño events superimposed on long-term increases in ambient temperature may alter dengue transmission when heavy precipitation events wash away breeding sites. Relationships between dengue in- cidence and El Niño episodes were recently demonstrated in a multi-country southeast Asian study examining monthly data on a regional level (van Panhuis et al., 2015). Dengue epidemic patterns were associated with periods of high temperature, peaking in 19 9 7–1998, a time coinciding with the strongest El Niño episode of the century. Cyclical, multi-annual epidemic cycles were also de- pendent on temperature. 5.2. Other drivers of dengue transmission In addition to weather and climate conditions, socioeconomic factors and public health determinants are important drivers of the spatial patterns of Aedesand dengue transmission. Changes in natural environments, such as from intensive farming, dams, irri- gation, unplanned urbanization, and increases in migration, travel, and trade can affect the distribution of vectors and the virus, for example by increasing the availability of breeding sites, or density of susceptible individuals. These interactions between climatic, so- cioeconomic, and other factors are complex, vary spatially and temporally, and can result in non-linear feedback. Many non-cli- matic factors, such as poor quality housing in urban areas, limited provision of safe water and improved sanitation, and limited access to waste management, would be expected to increase rather than reduce the effects of climate change, depending on the specific socioeconomic context (Campbell-Lendrum et al., 2015)(Fig. 3). Important factors for the spread ofAedesand dengue are global trade and travel. Concern over the introduction ofAe. albopictus and the subsequent outbreak of chikungunya in Italy led the Eur- opean Center for Disease Prevention and Control to quantify the relationship between the number of reported dengue cases im- ported into Europe and the volume of airline travelers arriving from dengue-affected areas internationally (Semenza et al., 2014). In 2010, over 5.8 million airline travelers entered Europe from areas affected by dengue, over 703,000 of whom arrived in 36 airports located in areas whereAe. albopictuswas recorded. By 2013, 38% more travelers arrived into those areas of Europe where Ae. albopictuswas recently introduced, highlighting the risk of local transmission (Semenza et al., 2014). 6. Projected climate change The 5th Assessment Report of the Intergovernmental Panel on Climate Change summarized observations over the past 150 years Fig. 3.Interaction of meteorological and other determinants of dengue transmission cycles and clinical disease. Source:World Health Organization and World Meteor- ological Organization (2012).K.L. Ebi, J. Nealon / Environmental Research 151 (2016) 115–12311 9 of changes in temperature and other weather variables, and pro- jected patterns of changes in weather over the course of this century based on modeling under different scenarios of green- house gas emissions (Intergovernmental Panel on Climate Change et al., 2013). Keyfindings were as follows: Since the 1950 s, many of the observed changes in temperature are unprecedented over decades to millennia. The globally averaged combined land and ocean surface temperature data show a warming of 0.85°C (90% likelihood range: 0.65–1. 0 6°C) over the period 1880–2012. Each of the last three decades was successively warmer at the earth’s surface than any preceding decade since 1850. In the Northern Hemisphere, 1983–2012 was likely the warmest 30-year period of the last 1400 years. It is highly probable that the number of cold days and nights decreased and the number of warm days and nights increased on the global scale. Human influence is considered likely to have contributed to observed global scale changes in the fre- quency and intensity of daily temperature extremes since the mid-20th century. Continued emissions of greenhouse gases will cause further warming and changes in all components of the climate system. Global surface temperature change for the end of the 21st century is likely to exceed 1.5°C relative to the period 1850– 1900, except under a very low emission scenario. It is virtually certain that there will be more frequent hot and fewer cold temperature extremes over most land areas on daily and sea- sonal timescales as global mean temperatures increase. 7. Dengue fever risk in a changing climate Messina et al. reviewed modeling studies that projected the future global distribution of dengue (Messina et al., 2015). The projections were difficult to compare because of the differing modeling approaches, the variable quality of the data used, and the different variables used to drive disease distribution. The spread, establishment, and persistence of dengue depend not only on weather-related variables but also on characteristics of the natural and man-made environments, particularly urbanization, and on travel and trade. Socioeconomic status may also alter the establishment of dengue; for example, an increased use of air conditioning could decrease vector-human interactions (Khormi and Kumar, 2012). Two basic modeling approaches are used to project the future geographic distribution and burden of dengue, often reaching dif- ferent conclusions (Messina et al., 2015). Biologically based (me- chanistic) approaches generally model the impact of weather vari- ables on the survival and competence ofAedes.Projected changes in weather variables under different scenarios of climate change are then used to estimate the future distribution and burden of dengue. Empirically based (statistical) approaches generally model re- lationships between locations of known dengue occurrence and factors associated with current patterns. Projected changes in these factors are used to estimate the future distribution and burden of dengue. Challenges to statistical modeling include the lack of vali- dated absence data for most locations (most vector surveys are conducted in known areas of transmission risk, not fringe areas of transmission) and the limited number of factors associated with dengue occurrence that have been projected more than a few years into the future. Further, because the risk of dengue is currently assessed based on past development patterns, such as water storage practices in low-income urban settings, the degree to which these relationships are predictive of future occurrence is unclear. Liu-Helmersson et al. recently developed a biological model that projected dengue epidemic potential in 10 European citiesbased on historic and projected temperature between 1901 and 2099 (Liu-Helmersson et al., to be published). Over the past dec- ade, relative vectorial capacity was not sufficiently high in Europe in the winter, spring, or autumn to allow dengue transmission, except for small areas in southern Europe during spring and au- tumn. During the summer, climatic conditions across Europe, not including the northern regions, are suitable for dengue epidemics. The intensity and duration of dengue transmission were predicted to rapidly increase over the course of the 21st century under a scenario of high greenhouse gas emissions and subsequent in- creases in temperature (Liu-Helmersson et al., to be published). Increasingly larger parts of Europe would have the potential for locally acquired dengue transmission, with a broader seasonal window, shouldAe. aegyptibe introduced. According to this model, by the end of this century, all studied cities could experi- ence epidemics of dengue, including Amsterdam, Berlin, London, and Stockholm. Campbell et al. used a statistical modeling approach (Campbell et al., 2015). They developed ecological niche models based onAe. aegyptiandAe. albopictusoccurrence data from 2013 and climatic variables, derived from monthly averages of maximum and mini- mum temperatures and precipitation for the period 1950–2000, to project the potential distributions of the vectors in 2050 under three scenarios of climate change. The models predicted the dis- tributional potential of the two species to be relatively stable over coming decades, with geographic expansions in many regions and contractions in others. Geographic distributions could shift when a mosquito species overcomes dispersal barriers to colonize new areas, and could expand along the current edges of its distribution when conditions became suitable for reproduction and growth. The models also suggested that these distribution patterns may become reorganized in response to the ecological niche profiles of the mosquitoes, which may have consequences for dengue trans- mission. Under a moderate emissions scenario, geographic ex- pansion was projected in eastern North America, farther south in South America, northward in southern Europe, more broadly in Central Africa, more broadly in East Asia, and across northern and eastern Australia (Fig. 4). Combining this information with pro- jected population change would give an indication of the potential increase in at-risk populations. Using another approach, Proestos et al. projected suitable glo- bal and regionalAe. albopictushabitats under a high emissions scenario and characterized uncertainty ranges using a fuzzy logic method to assess the influence of selected meteorological criteria (Proestos et al., 2015). Seven criteria were used to characterize a suitable habitat forAe. albopictus: annual average precipitation of Z200 mm; annual average temperature48.0°C; minimum temperature4 4.0°C in January (Northern hemisphere)/July (Southern Hemisphere); summer maximum temperature r40.0°C;Z60 days with41 mm rainfall; summer relative hu- midity ofZ30%; and winter relative humidityZ50%. Habitat suitability index was calculated using an equal weight, geometric mean combination of the seven meteorological variables. The projections indicated that in 2050, approximately 2.4 billion peo- ple could live in an area of highAe. albopictushabitat suitability; the land area was projected to be slightly smaller than the present day distribution, but projected population growth together with shifts in the geographic distribution would increase the risk of dengue. Monaghan et al. projected that by 2061–2080, the global land area suitable forAe. aegyptiwould increase 8% under moderate and 13% under high emissions pathways (Monaghan et al., 2016). The annual number of people exposed to the mosquito was pro- jected to increase by 8–12% when only considering climate change; by 59–65% when considering climate change and a de- velopment pathway associated with population growth that peaks K.L. Ebi, J. Nealon / Environmental Research 151 (2016) 115–123 120 mid-century and then declines; and by 127–134% when con- sidering climate change and a development pathway associated with high population growth. Regionally, Australia, Europe, and North America were projected to have the largest percentage in- creases in human exposure when only considering climate change. One of the few studies to explicitly consider the role of gross domestic product per capita (GDPpc), as a proxy for socioeconomic development, projected the future distribution of dengue in 2050 to be dependent on both climate and GDPpc under a moderate emissions scenario (Astrom et al., 2012). Based on an estimated 2.93 billion people currently at risk of dengue (48% of the world population), if GDPpc remains constant, climate change alone would increase the number of people at risk of dengue by 0.28 billion to 4.86 billion people or up to 56% of the world population projected in 2050. If climate and GDPpc change as projected, thenthe number of people at risk of dengue would decrease by 0.12 billion to 4.46 billion (52% of the world population), indicating that socioeconomic development could reduce some of the projected future risks of dengue with climate change. All of the studies evaluated by Messina et al. projected an in- crease in the overall global extent of dengue transmission, but the results did not agree with regard to the specific geographies where expansion or intensification would likely occur (Messina et al., 2015). The authors recommended improving the quality and quantity of disease occurrence data, along with uncertainty esti- mates. A better understanding is needed of the relative importance of various drivers of the distribution and burden of dengue, in- cluding human movement and shipping practices, and economic and population factors: future environmental suitability does not guarantee future disease presence (Morin et al., 2013). Fischer et al., Fig. 4.Potential geographic distribution patterns of a. Ae. aegypti and b. Ae. albopictus in 2050 under a moderate emissions scenario. Present day only distributional areas are in blue, with model agreement regarding stability of present day distributional areas shown by the intensity of blue shading (light blue denotes low and dark blue denotes high model agreement). Future distributional potential is shown as shades of orange (light orange denotes low and dark orange denotes high model agreement in projecting future suitability). Source:Campbell et al. (2015). (For interpretation of the references to color in thisfigure legend, the reader is referred to the web version of this article.)K.L. Ebi, J. Nealon / Environmental Research 151 (2016) 115–123121 reviewing mechanistic and correlative niche modeling approaches of future climate suitability ofAe. albopictusin Europe, re- commended that introduction gateways and dispersal pathways be considered in modeling future risks (Fischer et al., 2014). New climate change and assessment scenarios provide stan- dardized projections that could be used in future models of the risks of dengue transmission under different scenarios of climate and development (International committee, 2015). They also in- clude quantifications of some key variables and narratives of other important drivers, such as investments in improving health sys- tems in low- and middle-income countries (Ebi, 2014). These scenarios provide insights into global scale phenomena that will be key underlying drivers of the future distribution and burden of dengue, such as climate change, development, and demographic change, along with uncertainties in how these phenomena could evolve. 8. Conclusions Research indicates that the daily mean temperature and the variation in temperature are two of the most important drivers of the current distribution and incidence of dengue. Precipitation and precipitation extremes, whether associated with drought or excess rainfall, also affect mosquito abundance and arbovirus incidence. Studies generally project that, as temperatures continue to rise and precipitation patterns change, opportunities are increasing for further geographical expansion ofAedesvectors and of dengue. Expansion is primarily expected along the current edges of dengue distribution, with contraction in some areas where conditions would no longer be suitable forAedesreproduction and growth. Expansion could thus be expected to lead to a higher burden of dengue in low- and middle-income countries. Effective policies and measures will be key to prepare for and manage changes in the geographic range and incidence of the disease. These include improved and harmonized surveillance systems; implementation of vaccination campaigns in target areas; improved and evidence-based vector control; increased awareness of the disease and its broader impacts among the public and de- cision-makers; development of accurate early warning systems based on environmental and other factors to allow timely pre- ventive measures to be implemented; and increased support for research and development to better understand the current and likely future distributions ofAedesand DENV. Such initiatives re- quire coordination and, importantly, improved access to adapta- tion funds to help low- and middle-income countries prepare for changing burdens of dengue as temperature and precipitation patterns continue to change. Achieving improved dengue control is limited by inadequate investment in the necessary human and financial resources, and in research, education, training, and ca- pacity building. The current outbreak of Zika virus may lead to new and much needed resources, but only sustained and sus- tainable approaches will likely result in a future where dengue and other viruses carried byAedesbecome occasional nuisances rather than significant and expensive sources of morbidity and societal damage. Author contributions KE and JN jointly planned the scope and methods of the review. KE reviewed the literature, selected citations to include, and wrote the original report and this manuscript. JN critically reviewed and provided suggestions to improve the scientific content and clarity of the report. Both KE and JN edited thefinal version, and reviewed and guarantee the content of thefinal manuscript.Conflicts of interest KE received consulting fees for conducting the literature review and authoring the report. JN is employed by SanofiPasteur. Sanofi Pasteur commissioned and funded this review, and through JN was involved the decision to submit and in all stages of the preparation of this report. Acknowledgments The authors would like to thank Jean-Antoine Zinsou and Va- nina Laurent-Ledru, of SanofiPasteur, for their review and feed- back. Editing was performed by Juliette Gray of inScience, Springer Healthcare, London, UK, funded by SanofiPasteur. Appendix A. Supporting information Supplementary data associated with this article can be found in theonlineversionathttp://dx.doi.org/10.1016/j.envres.2016.07.026. References Achee, N.L., Gould, F., Perkins, T.A., Reiner Jr., R.C., Morrison, A.C., Ritchie, S.A., et al., 2015. A critical assessment of vector control for dengue prevention. PLoS Negl. Trop. Dis. 9 (5), e0003655. Aedes aegypti. Available online:〈http://ecdc.europa.eu/en/healthtopics/vectors/ mosquitoes/Pages/aedes-aegypti.aspx〉, accessed 26.11.15). Almeida, A.P., Goncalves, Y.M., Novo, M.T., Sousa, C.A., Melim, M., Gracio, A.J., 2007. Vector monitoring of Aedes aegypti in the autonomous region of madeira, Portugal. Eur. Surveill. 12 (11), E071115 071116. Andersson, N., Nava-Aguilera, E., Arostegui, J., Morales-Perez, A., Suazo-Laguna, H., Legorreta-Soberanis, J., et al., 2015. Evidence based community mobilization for dengue prevention in nicaragua and mexico (camino verde, the green way): Cluster randomized controlled trial. BMJ 351, h3267. Anez, G., Rios, M., 2013. Dengue in the united states of america: a worsening sce- nario? Biomed. Res Int. 2013, 678645. Astrom, C., Rocklov, J., Hales, S., Beguin, A., Louis, V., Sauerborn, R., 2012. Potential distribution of dengue fever under scenarios of climate change and economic development. Ecohealth 9 (4), 448–454. Bhatt, S., Gething, P.W., Brady, O.J., Messina, J.P., Farlow, A.W., Moyes, C.L., et al., 2013. The global distribution and burden of dengue. Nature 496 (7446), 504–507. Bowman, L.R., Runge-Ranzinger, S., McCall, P.J., 2014. Assessing the relationship between vector indices and dengue transmission: a systematic review of the evidence. PLoS Negl. Trop. Dis. 8 (5), e2848. Brady, O.J., Gething, P.W., Bhatt, S., Messina, J.P., Brownstein, J.S., Hoen, A.G., et al., 2012. Refining the global spatial limits of dengue virus transmission by evi- dence-based consensus. PLoS Negl. Trop. Dis. 6 (8), e1760. Brady, O.J., Golding, N., Pigott, D.M., Kraemer, M.U., Messina, J.P., Reiner Jr., R.C., et al., 2014. Global temperature constraints on Aedes aegypti and ae. Albopictus persistence and competence for dengue virus transmission. Parasit. Vectors 7, 338. Campbell, K.M., Lin, C.D., Iamsirithaworn, S., Scott, T.W., 2013. The complex re- lationship between weather and dengue virus transmission in thailand. Am. J. Trop. Med Hyg. 89 (6), 1066–1080. Campbell, L.P., Luther, C., Moo-Llanes, D., Ramsey, J.M., Danis-Lozano, R., Peterson, A.T., 2015. Climate change influences on global distributions of dengue and chikungunya virus vectors. Philos Trans. R. Soc. Lond. B Biol. Sci. 370 (1665). Campbell-Lendrum, D., Manga, L., Bagayoko, M., Sommerfeld, J., 2015. Climate change and vector-borne diseases: what are the implications for public health research and policy? Philos Trans. R. Soc. Lond. B Biol. Sci. 370 (1665). Carrington, L.B., Armijos, M.V., Lambrechts, L., Scott, T.W., 2013. Fluctuations at a low mean temperature accelerate dengue virus transmission by Aedes aegypti. PLoS Negl. Trop. Dis. 7 (4), e2190. Chan, M., Johansson, M.A., 2012. The incubation periods of dengue viruses. PLoS One 7 (11), e50972. Chien, L.C., Yu, H.L., 2014. Impact of meteorological factors on the spatiotemporal patterns of dengue fever incidence. Environ. Int. 73, 46–56. Christophers, S.R., 1960. Aëdes Aegypti Yellow Fever Mosquito. Cambridge Uni- versity Press, London, U.K.. Dengue–entomology & ecology. Available online:〈http://www.cdc.gov/dengue/ entomologyEcology/〉, (accessed 26.11.15). Ebi, K.L., 2014. Health in the new scenarios for climate change research. Int. J. En- viron. Res Public Health 11 (1), 30–46. Estallo, E.L., Luduena-Almeida, F.F., Introini, M.V., Zaidenberg, M., Almiron, W.R., K.L. Ebi, J. Nealon / Environmental Research 151 (2016) 115–123 122 2015. Weather variability associated with aedes (stegomyia) aegypti (dengue vector) oviposition dynamics in northwestern argentina. PLoS One 10 (5), e0127820. Fischer, D., Thomas, S.M., Neteler, M., Tjaden, N.B., Beierkuhnlein, C., 2014. Climatic suitability of Aedes albopictus in europe referring to climate change projec- tions: Comparison of mechanistic and correlative niche modelling approaches. Eur. Surveill. 19 (6). Global alert and response–impact of dengue. Available online:〈http://www.who. int/csr/disease/dengue/impact/en/〉, (accessed 27.07.15). Grunnill, M., Boots, M., 2016. How important is vertical transmission of dengue viruses by mosquitoes (diptera: Culicidae)? J. Med Entomol. 53 (1), 1–19. Intergovernmental Panel on Climate Change, 2013. Summary for policymakers. In: Stocker, T.F.Q.D., Plattner, G.-K., Tignor, M., Allen, S.K., Boschung, J., Nauels, A., Xia, Y., Bex, V., Midgley, P.M. (Eds.), Climate change 2013: The Physical Science Basis. Contribution of Working Group i to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, United Kingdom and New York, p. 28. International committee on new integrated climate change assessment scenarios. Available online:〈https://www2.cgd.ucar.edu/research/iconics/publications/ ssps-climate-change-research〉, (accessed 02.12.15). Khormi, H.M., Kumar, L., 2012. Assessing the risk for dengue fever based on so- cioeconomic and environmental variables in a geographical information system environment. Geospat Health 6 (2), 171–17 6. Kolivras, K., 2010. Changes in dengue risk potential in hawaii, USA, due to climate variability and change. Clim. Res. 42, 1–11. Kraemer, M.U., Sinka, M.E., Duda, K.A., Mylne, A.Q., Shearer, F.M., Barker, CM., et al., 2015. The global distribution of the arbovirus vectors aedes aegypti and ae. Albopictus. Elife, vol. 4. pp. e08347. Kutsuna, S., Kato, Y., Moi, M.L., Kotaki, A., Ota, M., Shinohara, K., et al., 2015. Au- tochthonous dengue fever, tokyo, japan, 2014. Emerg. Infect. Dis. 21 (3), 517–520. Lambrechts, L., Paaijmans, K.P., Fansiri, T., Carrington, L.B., Kramer, L.D., Thomas, M. B., et al., 2011. Impact of daily temperaturefluctuations on dengue virus transmission by Aedes aegypti. Proc. Natl. Acad. Sci. U S A 108 (18), 7460–7465. Liu-Helmersson, J., Stenlund, H., Wilder-Smith, A., Rocklov, J., 2014. Vectorial ca- pacity of Aedes aegypti: effects of temperature and implications for global dengue epidemic potential. PLoS One 9 (3), e89783. Liu-Helmersson, J., Quam, M., Wilder-Smith, A., Stenlund, H., Ebi, K., Massad, E., et al., 2016. Climate change andAedesvectors: 21st century projections for dengue transmission in Europe. EBioMedicine 7, 267–277. Messina, J.P., Brady, O.J., Pigott, D.M., Golding, N., Kraemer, M.U., Scott, T.W., et al., 2015. The many projected futures of dengue. Nat. Rev. Micro. 13 (4), 230–239. Monaghan, A.J., Morin, C.W., Steinhoff, D.F., Wilhelmi, O., Hayden, M., Quattrochi, D. A., et al., 2016. On the seasonal occurrence and abundance of the zika virus vector mosquito Aedes aegypti in the contiguous united states. PLoS Curr. 8. Morin, C.W., Comrie, A.C., Ernst, K., 2013. Climate and dengue transmission: evi- dence and implications. Environ. Health Perspect. 121 (11–12), 1264–1272. Murray, N.E., Quam, M.B., Wilder-Smith, A., 2013. Epidemiology of dengue: past, present and future prospects. Clin. Epidemiol. 5, 299–309. Proestos, Y., Christophides, G.K., Erguler, K., Tanarhte, M., Waldock, J., Lelieveld, J., 2015. Present and future projections of habitat suitability of the asian tigermosquito, a vector of viral pathogens, from global climate simulation. Philos Trans. R. Soc. Lond. B Biol. Sci. 370 (1665). Racloz, V., Ramsey, R., Tong, S., Hu, W., 2012. Surveillance of dengue fever virus: a review of epidemiological models and early warning systems. PLoS Negl. Trop. Dis. 6 (5), e1648. Radke, E.G., Gregory, C.J., Kintziger, K.W., Sauber-Schatz, E.K., Hunsperger, E.A., Gallagher, G.R., et al., 2012. Dengue outbreak in key west,florida, USA, 2009. Emerg. Infect. Dis. 18 (1), 135–137. Ramos, M.M., Mohammed, H., Zielinski-Gutierrez, E., Hayden, M.H., Lopez, J.L., Fournier, M., et al., 2008. Epidemic dengue and dengue hemorrhagic fever at the texas-mexico border: Results of a household-based seroepidemiologic survey, december 2005. Am. J. Trop. Med Hyg. 78 (3), 364–369. Rogers, D.J., 2015. Dengue: recent past and future threats. Philos Trans. R. Soc. Lond. B Biol. Sci. 370 (1665). Rohani, A., Wong, Y.C., Zamre, I., Lee, H.L., Zurainee, M.N., 2009. The effect of ex- trinsic incubation temperature on development of dengue serotype 2 and 4 viruses in Aedes aegypti (l.). Southeast Asian J. Trop. Med Public Health 40 (5), 942–950. Scholte, E., Den Hartog, W., Dik, M., Schoelitsz, B., Brooks, M., Schaffner, F., et al., 2010. Introduction and control of three invasive mosquito species in the netherlands, july-october 2010. Eur. Surveill. 15 (45). Semenza, J.C., Sudre, B., Miniota, J., Rossi, M., Hu, W., Kossowsky, D., et al., 2014. International dispersal of dengue through air travel: Importation risk for eur- ope. PLoS Negl. Trop. Dis. 8 (12), e3278. Shepard, D., Halasa, Y., Undurraga, E., 2014. Global cost of dengue in the profes- sional healthcare system. Annual meeting of the American Society of Tropical Medicine and Hygiene. New Orleans, Louisiana, USA. Shepard, D., Halasa, Y., Undurraga, E., 2015. Stanaway J. Global economic cost of dengue illness American Society of Tropical Medicine and Hygiene. Philadel- phia, USA. Stahl, H.C., Butenschoen, V.M., Tran, H.T., Gozzer, E., Skewes, R., Mahendradhata, Y., et al., 2013. Cost of dengue outbreaks: literature review and country case stu- dies. BMC Public Health 13, 1048. Tun-Lin, W., Burkot, T.R., Kay, B.H., 2000. Effects of temperature and larval diet on development rates and survival of the dengue vector Aedes aegypti in north queensland, australia. Med Vet. Entomol. 14 (1), 31–37. van Panhuis, W.G., Choisy, M., Xiong, X., Chok, N.S., Akarasewi, P., Iamsirithaworn, S., et al., 2015. Region-wide synchrony and traveling waves of dengue across eight countries in southeast asia. Proc. Natl. Acad. Sci. USA 112 (42), 13 0 6 9–13074. Vasseur, D.A., DeLong, J.P., Gilbert, B., Greig, H.S., Harley, C.D., McCann, K.S., et al., 2014. Increased temperature variation poses a greater risk to species than cli- mate warming. Proc. Biol. Sci. 281 (1779), 20132612. Wilder-Smith, A., 2012. Dengue infections in travellers. Paediatr. Int. Child. Health 32 (s1), 28–32. World Health Organization, 2012. Global strategy for dengue prevention and con- trol, 2012–2020. 6. WHO, Geneva, p. 43. World Health Organization and World Meteorological Organization, 2012. Atlas of health and climate. Geneva, Switzerland: World Health Organization and World Meteorological Organization. p. 21. K.L. Ebi, J. Nealon / Environmental Research 151 (2016) 115–123123
Please help me out with this assignment, case study 3. You can use the articles and graphs on “case study 3“ file to finish this assignment. Thanks.
www.thelancet.com/infection Published online April 15, 2016 http://dx.doi.org/10.1016/S1473-3099(16)00146-8 1 Articles The global economic burden of dengue: a systematic analysis Donald S Shepard, Eduardo A Undurraga, Yara A Halasa, Jeff rey D Stanaway Summary Background Dengue is a serious global burden. Unreported and unrecognised apparent dengue virus infections make it diffi cult to estimate the true extent of dengue and current estimates of the incidence and costs of dengue have substantial uncertainty. Objective, systematic, comparable measures of dengue burden are needed to track health progress, assess the application and fi nancing of emerging preventive and control strategies, and inform health policy. We estimated the global economic burden of dengue by country and super-region (groups of epidemiologically similar countries). Methods We used the latest dengue incidence estimates from the Institute for Health Metrics and Evaluation’s Global Burden of Disease Study 2013 and several other data sources to assess the economic burden of symptomatic dengue cases in the 141 countries and territories with active dengue transmission. From the scientifi c literature and regressions, we estimated cases and costs by setting, including the non-medical setting, for all countries and territories. Findings Our global estimates suggest that in 2013 there were a total of 58∙40 million symptomatic dengue virus infections (95% uncertainty interval [95% UI] 24 million–122 million), including 13 586 fatal cases (95% UI 4200–34 700), and that the total annual global cost of dengue illness was US$8∙9 billion (95% UI 3∙7 billion–19∙7 billion). The global distribution of dengue cases is 18% admitted to hospital, 48% ambulatory, and 34% non-medical. Interpretation The global cost of dengue is substantial and, if control strategies could reduce dengue appreciably, billions of dollars could be saved globally. In estimating dengue costs by country and setting, this study contributes to the needs of policy makers, donors, developers, and researchers for economic assessments of dengue interventions, particularly with the licensure of the fi rst dengue vaccine and promising developments in other technologies. Funding Sanofi Pasteur. Introduction Dengue is the most important mosquito-borne viral disease, with approximately half of the world’s population living in dengue-endemic countries, and it is rapidly spreading. 1,2 Although dengue represents a serious global economic and disease burden, 3–5 un- recognised and unreported apparent dengue virus infections, and questions about data access and quality, make it diffi cult to estimate the true extent of dengue illness. 1,6,7 Alternative sources estimate the annual number of symptomatic dengue cases globally to be 9 million, 8 50 million–100 million, 9 3∙2 million (reported), 10–12 and 96 million. 1 Published studies 3,13 about the economic burden of dengue are sparse, and country-level cost estimates are only available for a small portion of endemic countries. 14 The biggest challenges in dengue burden estimates include deriving the actual number of dengue cases and dengue cost per case, even in countries in which studies have been done, and extrapolating from those countries to other locations. 7 Objective, systematic, and comparable measures of dengue burden are needed to track health progress, assess the application and fi nancing of emerging preventive and control strategies, and to inform evidence- based policy. 7 In a published study with other colleagues, 15 we estimated the number of dengue cases by country and super-region in 2013. Here, we present the results of a parallel study in which, by integrating data from various sources, we estimate the global economic burden of dengue by country and super-region with associated uncertainty intervals (UI). Methods Overall analysis For this systematic analysis, we obtained data for the number of cases from our global burden of dengue analysis. 15 The distribution of cases between medical and non-medical settings was derived from national surveys of febrile illness and use of formal health care for selected countries, whereas the distribution within medical settings (admitted to hospital vs ambulatory) was inferred from previously published dengue studies. Numbers of dengue deaths were calculated by applying a case fatality rate to the estimated numbers of cases by country. The age distribution of dengue deaths was extrapolated from available country data. Economic costs per case were derived from published studies of dengue costs, an expert survey, and national economic data. For each variable in the estimation, we identifi ed countries with empirical estimates and the patterns in those estimates in relation to variables available for all countries with dengue—population, gross domestic product (GDP) per head, or previously derived variables. Lancet Infect Dis 2016 Published Online April 15, 2016 http://dx.doi.org/10.1016/ S1473-3099(16)00146-8 See Online/Commenthttp://dx.doi.org/10.1016/ S1473-3099(16)30001-9 Schneider Institutes for Health Policy, Heller School for Social Policy and Management, Brandeis University, Waltham, MA, USA (Prof D S Shepard PhD, E A Undurraga PhD, Y A Halasa DDS); and Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA ( J D Stanaway PhD) Correspondence to: Prof Donald S Shepard, Schneider Institutes for Health Policy, Heller School for Social Policy and Management, Brandeis University, Waltham, MA, USA [email protected] Articles 2 www.thelancet.com/infection Published online April 15, 2016 http://dx.doi.org/10.1016/S1473-3099(16)00146-8 We then used the pattern to predict values for remaining countries. We selected independent variables based on their availability for all countries and territories, statistically signifi cant association with the outcome, biological or economic plausibility, and parsimony (fi gure 1). Estimation of symptomatic dengue cases Our estimate of the number of dengue cases in 141 countries and territories is a component of the Global Burden of Disease Study 2013 (GBD 2013). 16 We adjusted for potential under-reporting using a modelling Dengue occurrence probability 1 Population density (gridded world population) Dengue score Estimates of dengue under-reporting (published literature) Reported dengue episodes (WHO, Ministry of Health national statistics, published literature) Adjusted estimates of dengue incidence (non-fatal) Estimates of total dengue episodes by country (Institute for Health Metrics) 15 Institute for Health Metrics CODEm death estimates Literature review: economics of dengue by treatment setting Direct and indirect cost per case by treatment setting Expert panel: share of non-medical patients who spent money and their average expenditures Dengue incidence by treatment setting Economic burden of dengue = Σi cost per case in setting i × cases in setting i with i (setting) = fatal, non-fatal cases admitted to hospital, ambulatory, and non-medical cases Estimates of the economic burden of dengue by treatment setting Figure 1: Flow chart of key steps in estimating the global economic burden of dengue CODEm is the Cause-of-Death Ensemble Model tool. Dengue score is a country-level index of dengue transmission. The study by Stanaway and colleagues 15 and its appendix provide further details. Specifi c details about each step in the fl ow chart are given in the appendix. After the summation sign, “i” is the dengue-endemic country or territory for which we estimated the economic burden of dengue by treatment setting. Research in context Evidence before this study The true extent of dengue burden has been underestimated. Objective, systematic, comparable measures of dengue burden are needed to track health progress, assess the application and fi nancing of emerging preventive and control strategies, and, more generally, to inform evidence-based health policy. We searched the Web of Science, Medline, or in WHO’s Dengue Bulletin for articles published between 1995 and 2015 in English, Spanish, French, or Portuguese, using the keyword “dengue” and any of the following list of keywords: surveillance, incidence, reporting, sensitivity, capture recapture, cohort, economics, costs, burden, Aedes aegypti, and control. Added value of this study We systematically assembled and analysed the latest estimates from the Institute for Health Metrics and Evaluation’s Global Burden of Disease Study, World Bank Indicators, Demographic and Health Surveys, published literature through systematic reviews and responses to an expert panel questionnaire to assess the global economic and disease burden of dengue illness. We cover all 141 countries and territories with active dengue transmission. Our global estimates suggest that in 2013 there were a total of 5840 million symptomatic dengue virus infections, including 13 586 fatal cases. The total annual global cost of dengue illness was US$8·89 billion: 46·0% from non-fatal cases admitted to hospital, 33·6% from non-fatal ambulatory cases, 8·5% from non-fatal non-medical cases, and 11·9% for fatal cases. Data limitations create uncertainty around all of these estimates. Our study’s main contribution is providing comparable, consistent estimates of the economic burden of dengue by treatment setting and by country, region, and globally. Our study endeavors to inform policy analyses with the most comprehensive economic assessment of dengue to date. Implications of all the available evidence The global cost of dengue is substantial. Recommended approaches to improve future estimates include merging multiple data sources, such as cohort and surveillance data, adjusting for unrecognised dengue cases, and modelling to estimate dengue incidence in locations with limited data. Our hope is that improved estimates and a greater understanding of the main factors driving uncertainty around the burden of dengue will enable improvement of current estimates, and consequently, improve the assessment of existing and potential future preventive and treatment approaches. Articles www.thelancet.com/infection Published online April 15, 2016 http://dx.doi.org/10.1016/S1473-3099(16)00146-8 3 See Online for appendix approach where we defi ned the expected spatial distribution of dengue virus for 2013, modelled the association between this expected distribution and reported incidence with the assumption that deviations from the expected distribution refl ect deviations in completeness of reporting, and calibrated the model by benchmarking these deviations against published empirical expansion factors, and removed countries with no evidence of dengue virus transmission. 15 We also incorporated small island countries and territories (appendix pp 3, 4, and 10–34). Estimation of dengue cases by setting We divided symptomatic dengue cases into three groups on the basis of the most costly treatment setting used: hospital admission, including any ambulatory visits the patient might have had before or after the admission; ambulatory, consisting of patients who consulted a health professional (such as a physician, nurse, or medical offi cer) or health facility (including hospitals’ emergency and outpatient departments, health centres, clinics, and clinicians’ private offi ces); and non-medical cases (ie, patients outside the professional sector who received 3001–5000 1501–3000 1001–1500 751–1000 501–750 301–500 1–300 0 $15.01–$55.00 $5.01–$15.00 $2.51–$5.00 $1.01–$2.50 $0.51–$1.00 $0.11–$0.50 $0.01–$0.10 $0.00 A B Figure 2: Dengue incidence per 100 000 population (A) and cost per head of symptomatic dengue infections (2013 US$; B) Articles 4 www.thelancet.com/infection Published online April 15, 2016 http://dx.doi.org/10.1016/S1473-3099(16)00146-8 neither diagnosis nor treatment from a health professional or facility, although such patients might have had laboratory testing or purchased a therapeutic product on their own initiative). We distributed cases between hospital and ambulatory settings for patients treated in the professional health sector from previous empirical studies and regression estimates (appendix p 5). Research suggests that a substantial proportion of dengue cases are not treated in the professional health sector because of limited access to primary care, limited operating hours, costs, alternative health-care providers, or milder dengue cases. 7 We derived the percentage of cases treated outside the professional health-care sector using the proportion of fever cases in 3-year-old children treated in the formal health sector as a proxy 17 (appendix pp 4, 5). Estimation of deaths due to dengue virus infection To estimate the number of fatal dengue virus infections, we collected country-level reported dengue cases from 2000 to 2014 compiled from national vital registrations and calculated the ratio of reported deaths to reported cases admitted to hospital for these countries. We obtained annual reported fatal dengue cases for 45 countries. Assuming that all fatal dengue cases occur in hospitals and that the rates of reporting of fatal and non-fatal dengue cases admitted to hospital were similar, we adjusted reported deaths based on 32 country-specifi c expansion factors for cases admitted to hospital obtained from previous studies in Asia and the Americas 4,18–20 (appendix p 5, 6, and 50). Estimation of the cost of dengue We considered two types of cost in our analysis, short- term and long-term cost. Short-term cost relates to non- fatal dengue episodes, consists of direct medical and non-medical cost, and indirect cost associated with time lost because of illness or care. Long-term costs relate to fatal dengue episodes. Direct and indirect costs (in 2013) of cases admitted to hospital and ambulatory dengue cases were obtained from empirical studies in 47 countries in the Americas, southeast Asia, and India, supplemented by regression analyses (appendix pp 40–42). We estimated direct medical expenditure based on the responses to our expert panel questionnaire by 24 experts from nine countries from the Americas and Asia, which provided insights from academic, public, and private perspectives from public offi cials, clinicians, and researchers of dengue we had been involved with in previous dengue-related collaborations. We responded to their questions and comments, aggregated their responses from a single round of inquiry, and generalised the fi ndings on the basis of a measure of health-care accessibility (appendix pp 42–49). We used the human capital approach. This method estimates the economic value of human life lost due to premature death based on the discounted present value of that person’s expected productivity. We then estimated the average discounted life expectancy for children and adults on the basis of the WHO life tables 21 and valued each year at the country’s GDP per head (appendix pp 5, 6, 53). Sensitivity analysis GBD 2013 accounted for uncertainty through posterior simulations based on 1000 random draws of each incidence rate estimate for each country. 15,16 For con- sistency, we addressed uncertainty in our case distribution, death from dengue, and cost estimates, using Monte Carlo simulations with 1000 repetitions with 1000 random draws of each number of dengue cases per country generated by GBD 2013 (appendix pp 50–53). Role of the funding source The funder of the study off ered optional comments on an earlier draft of this study but otherwise had no role in study design, data collection, data analysis, data interpretation, 20 40 60 80 Non-fatal cases admitted to hospital Fatal cases Ambulatory Non-medical Global total Central and eastern Europe, central Asia High-income countries Latin America and the Caribbean North Africa and the Middle East South Asia Southeast and east Asia and Oceania Saharan Africa 18% 48% 34% 100 0 Distribution of dengue cases* (%) A 20 40 60 80 Global total Central and eastern Europe, central Asia High-income countries Latin America and the Caribbean North Africa and the Middle East South Asia Southeast and east Asia and Oceania Saharan Africa 12% 46% 34% 8% 100 0 Distribution of dengue costs (%) B Figure 3: Estimated number of dengue episodes (A) and aggregate costs (B) of dengue by treatment setting Non-medical denotes dengue episodes treated outside the professional health-care sector. *Fatal cases are too small relative to total symptomatic dengue episodes to appear in the fi gure; however, fatal episodes represent a substantial share of the total costs (B). Articles www.thelancet.com/infection Published online April 15, 2016 http://dx.doi.org/10.1016/S1473-3099(16)00146-8 5 or writing of the report. The corresponding author had full access to all the data in the study and had fi nal responsibility for the decision to submit for publication. Results With use of results from GBD 2013, we estimated that 58∙40 million dengue cases (95% UI 24 million–122 million) occurred in 2013 in 141 countries with dengue virus transmission. We estimated that, of these, 10∙5 million were treated in the hospital setting and 28∙1 million were treated in the ambulatory health-care setting, and 19∙7 million remained outside the health-care system. The incidence of dengue is mapped in fi gure 2, and reported by super-region and country (appendix pp 10–15 and 35). The distribution of dengue cases by treatment setting is shown in fi gure 3. With use of the adjusted number of dengue deaths and the number of dengue cases for the 32 countries with reported deaths and hospital expansion factors (used to adjust for under-reporting of symptomatic dengue infections), we estimated a ratio of one death per 5991 dengue cases in these 32 countries and applied this ratio to the remaining countries. We estimated a global total of 13 586 dengue deaths (95% UI 4200–34 700) in 2013, with 5838 deaths occurring in children and 7748 in adults (appendix pp 7–36). Our estimated global average cost per dengue case is US$70∙10 (95% UI 66∙66–74∙63) for cases admitted to hospital, $51∙16 (49∙80–53∙71) for ambulatory cases, $12∙94 (12∙80–13∙73) for cases outside the health-care sector, and $84 730 (68 622–108 165) for fatal cases ($80 414 [74 000–95 000] for children and $75 820 [62 000–121 000] for adults). The grand weighted average across all types of cases is $151 (134–177). Costs per case are generally higher in high-income super-regions and range from a low of $56 (46–82) in sub-Saharan Africa to a high of $1146 (765–1639) in the high-income super-region (table). Similarly, we see the highest costs per case in high-income countries, such as the USA and Australia, and the lowest costs per case in low-income countries in Asia and sub-Saharan Africa (appendix pp 7–36). Each childhood dengue death represented 28∙8 discounted (67∙9 undiscounted) years, and each adult death lost meant 18∙8 discounted (32∙2 undiscounted) expected years lost. Figure 2 shows the cost of dengue per capita by country in 2013 and fi gure 3 shows the distribution of costs by treatment setting. We obtained a total annual global aggregate cost of dengue in 2013 of $8∙9 billion (95% UI 3∙7 billion–19∙7 billion; appendix pp 22–36) or $1∙56 per capita for 141 dengue endemic countries with aggregate costs of non-fatal cases admitted to hospital ($4093 million), ambulatory non-fatal cases ($2987 million), non-medical cases ($752 million), and fatal cases ($1055 million). Individual country estimates are shown in the appendix (pp 22–34). Discussion On the basis of 58∙40 million global dengue cases, we estimated 10∙53 million cases admitted to hospital, 13 586 fatal cases, and a total annual global aggregate cost of dengue illness of $8∙9 billion in 2013. Point estimates for many countries might not be precise because they are based on extrapolations with available data. A range of factors, including limited availability and quality of surveillance data in many countries and few studies on the distribution of treat ment settings, contributed to the variability in previous estimates of the global burden of dengue illness and the wide uncertainty intervals for our estimates. The biggest payoff for improving burden of Short-term costsLong-term costs Overall Direct hospital Direct ambulatoryDirect outside medical sectorIndirect hospitalIndirect ambulatoryIndirect outside medical sectorIndirect fatal child Indirect fatal adult Central Europe, eastern Europe, and central Asia$243 (188–343)$40 (32–54)$3 (1–9)$44 (30–71)$24 (18–38)$40 (28–62)$78 003 (66 187–102 129)$59 130 46 995–109 490)$91 (73–137) High-income* $2427 (1637–3484)$253 (170–337)$6 (2–22)$1382 (844–2152)$425 (253–627)$458 (270–695)$800 767 (590 462–979 984)$616 508 (484 101–892 406)$1146 (765–1639) Latin America and the Caribbean$1000 (773–1251)$102 (88–120)$9 (6–14)$360 (271–471)$161 (128–211)$141 (115–185)$184 805 (164 112–257 764)$169 577 (130 269–274 864)$307 (262–382) North Africa and the Middle East$281 (220–369)$46 (37–60)$7 (5–12)$52 (38–72)$29 (21–40)$25 (19–34)$78 647 (72 535–86 738)$58 437 (49 177–87 441)$102 (81–137) South Asia $241 (159–366)$25 17–37)$4 (1–8)$19 (11–31)$10 (6–17) $10 (6–16)$34 803 (31 576–39 529)$24 345 (20 174–39 773)$74 (50–116) Southeast Asia, east Asia, and Oceania$376 (313–476)$78 (68–93)$9 (4–10)$71 (57–94)$39 (33–50)$41 (34–52)$98 365 (88 698–114 105)$86 136 (72 345–143 209)$207 (176–255) Sub-Saharan Africa $179 (152–232)$29 ($25–$38)$8 (5–13)$27 (21–37)$15 (12–21)$18 (13–25)$47 905 ($42 454–$57 622)$40 461 (33 175–67 528)$56 (46–82) Global average $333 (283–403)$60 (54–68)$7 (4–8)$56 (46–70)$46 (40–56)$31 (27–38)$80 414 (74 455–95 078)$75 820 (62 281–120 501)$152 (136–179) *High-income regions include Argentina, Australia, Brunei Darussalam, Singapore, and the USA. Table: Weighted average costs of illness and 95% uncertainty intervals per dengue case summarised by super-region in 2013 Articles 6 www.thelancet.com/infection Published online April 15, 2016 http://dx.doi.org/10.1016/S1473-3099(16)00146-8 dengue estimates would come from studies that can link and analyse existing data. 7 To our knowledge, only one previous publication has estimated the global economic burden of dengue. 14 In view of the many sources of uncertainty, we think it is useful to develop alternative approaches to estimating the economic burden of dengue. We believe that the main strengths of our approach relate to the com- prehensive use of all relevant empirical data and systematic analysis, our inclusion of all countries believed to have dengue transmission, and our quanti- fi cation of the resulting uncertainty. We obtained direct and indirect costs per dengue case based on empirical estimates from previous studies from various settings in 14 dengue-endemic countries. Similarly, we esti- mated the total number of deaths based on reported cases of dengue, and adjusted reported cases based on reporting rates from cases admitted to hospital. This assumption is consistent with the limited available evidence that suggests substantial under-reporting even in high-income areas. 7 Our results show higher indirect cost for a fatal child case compared with a fatal adult case because of the fact that children lose more life- years by premature death due to dengue than do adults. Our estimates of cost are about a quarter of those obtained by Selck and colleagues 14 of $39∙30 billion in 2010 for four main reasons. First, we used a diff erent severity mix, and thus a mix of treatment settings (Selck and colleagues 14 report more severe cases and assume that all cases presented to the professional health-care sector). Second Selck and colleagues 14 estimated about 74 000 annual fatal dengue episodes, about six times our estimate, and almost four times WHO’s estimate of up to 20 000 annual deaths. 9 Third, Selck and colleagues 14 reported a substantially higher average cost of $414 per symptomatic dengue cases compared with our global average estimate of $152 (95% UI 136–179). Finally, their analysis used Bhatt and colleagues, 1 incidence estimates and appeared to assume that every case received care in some kind of formal setting, 14 whereas our global estimate is substantially lower because we recognised non-medical episodes and resource constraints in most health systems. We did several sensitivity analyses. We fi rst repeated our analysis using Bhatt and colleagues’ 1 estimates of dengue incidence, which resulted in a 54% increase above our estimates of economic burden (Bhatt and colleagues: $13∙66 billion; Stanaway and col- leagues: 15 $8∙89 billion). We next assumed that the direct medical cost for those treated outside the professional health-care sector was similar to those who sought treatment in ambulatory settings, fi nding increases over our current estimate of 10% with the incidence estimated by Stanaway and colleagues 15 and 70% with Bhatt and colleagues’ 1 incidence estimates. We estimated the total cost of dengue illness in Latin America and the Caribbean to be about $1∙73 billion annually, which is lower than our previous estimate of the average cost of dengue illness in the Americas of $2∙15 billion in 2010. 4 This is because of developments in our methods—ie, we have adjusted for the fact that not all dengue cases will be treated in the professional health- care sector. In this study, we captured the cost associated with treatment outside the professional health-care system. However, results of this analysis in 12 southeast Asian countries (fi gure 3) suggest that costs per head are higher than a previous published estimate for these countries ($2∙38 [95% UI 0∙93–5∙33] per head) 5 because of new techniques for estimating numbers of dengue cases, 15 a mostly newer reference period (2000–2010 vs 1988–2013) as dengue has increased, and additional data for cost per case. If the share of cases admitted to hospital were higher than our estimate, then the global cost of dengue would have been higher than that reported here. If the share of ambulatory cases were higher, then global cost of dengue would be lower than our estimate. Our estimates of annual dengue cases are based on a model that took reporting data from 1988 through to 2013, which smoothed out the eff ects of dengue outbreaks, making our estimates more representative of an average year. However, despite the refi nements in this study, several factors make our estimates conservative. First, we might have underestimated the share of dengue patients treated in the formal health sector. Our estimates of this share are based on rates for 3-year-old children, mostly in countries in which malaria is prominent. Adults and older children might be more likely than young children to be admitted to hospital. Second, our estimate of economic costs is based on human capital. Estimates based on willingness to pay are generally higher. Limitations of our study include insuffi cient incidence data from Africa and our reliance on data from Latin America to distribute dengue cases among hospital, ambulatory, and non-medical settings based on experts participating in an expert survey, restricted or delayed access to some surveillance data, limited information or imprecise diagnosis of dengue-related deaths, 22 few covariates to extrapolate the distribution of fatal cases between children and adults to estimate indirect costs from fatal episodes, and the exclusion of vector control and surveillance cost data from the analysis. In some countries, not all the population is at risk (eg, only 68% in Mexico and 53% in Colombia). The incidence rates calculated might therefore be underestimated, and consequently, the overall economic burden of dengue. Because of a paucity of empirical data in some regions, such as Africa and the Middle East and wide annual variation in dengue incidence, our estimates for some countries in 2013 might be too high or too low, since the estimation model smooths variation across years towards the mean value, rather than estimating annual fl uctuations. We did an extensive sensitivity analysis to address these sources of uncertainty (appendix pp 50–53). Other costs associated with dengue fever were also not considered because the data are non-existent or too sparse Articles www.thelancet.com/infection Published online April 15, 2016 http://dx.doi.org/10.1016/S1473-3099(16)00146-8 7 9 World Health Organization. Dengue control. 2015. http://www.who. int/denguecontrol/en/ (accessed April 24, 2015). 10 World Health Organization Western Pacifi c Region. Annual dengue data in the Western Pacifi c Region. WPRO. 2014. http://www.wpro. who.int/emerging_diseases/annual.dengue.data.wpr/en/ (accessed June 24, 2015). 11 Pan American Health Organization. Epidemiological surveillance of rabies in the Americas. 2015. http://siepi.panaftosa.org.br/Panel. aspx (accessed Aug 25, 2015). 12 World Health Organization Regional Offi ce for South-East Asia. Health topics. Dengue. 2015. http://www.searo.who.int/topics/ dengue/en/ (accessed June 24, 2015). 13 Constenla D, Garcia C, Lefcourt N. Assessing the economics of dengue: results from a systematic review of the literature and expert survey. Pharmacoeconomics 2015; 33: 1107–35. 14 Selck FW, Adalja AA, Boddie CR. An estimate of the global health care and lost productivity costs of dengue. Vector Borne Zoonotic Dis 2014; 14: 824–26. 15 Stanaway JD, Shepard DS, Undurraga EA, et al. The global burden of dengue: a systematic analysis from the Global Burden of Disease Study 2013. Lancet Infect Dis 2016; published online Feb 10. http://dx.doi.org/10.1016/S1473-3099(16)00026-8. 16 Vos T, Barber RM, Bell B, et al. Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 2015; 386: 743–800. 17 Demographic and Health Surveys (DHS). STAT compiler. 2015. http://www.statcompiler.com/ (accessed Jan 12, 2015). 18 Shepard DS, Halasa YA, Tyagi BK, et al. Economic and disease burden of dengue illness in India. Am J Trop Med Hyg 2014; 91: 1235–42. 19 Undurraga EA, Halasa YA, Shepard DS. Use of expansion factors to estimate the burden of dengue in Southeast Asia: a systematic analysis. PLoS Negl Trop Dis 2013; 7: e2056. 20 Undurraga EA, Betancourt-Cravioto M, Ramos-Castañeda J, et al. Economic and disease burden of dengue in Mexico. PLoS Negl Trop Dis 2015; 9: e3547. 21 World Health Organization. Life tables by country. 2015. http://apps. who.int/gho/data/view.main.60000?lang=en (accessed Feb 1, 2015). 22 Pamplona LG, de Melo Braga DN, da Silva LMA, et al. Postmortem diagnosis of dengue as an epidemiological surveillance tool. Am J Trop Med Hyg 2016; 94: 187–92. 23 Barnighausen T, Bloom DE, Cafi ero ET, O’Brien J. Valuing the broader benefi ts of dengue vaccination, with a preliminary application to Brazil. Semin Immunol 2013; 25: 104–13. 24 World Health Organization. Dengue haemorrhagic fever: diagnosis, treatment, prevention and control. 1997. http://www.who.int/csr/ resources/publications/dengue/Denguepublication/en/ (accessed Oct 21, 2012). 25 Tiga DC, Undurraga EA, Ramos-Castañeda J, Martínez-Vega R, Tschampl CA, Shepard D. Persistent symptoms of dengue: estimates of the incremental disease and economic burden in Mexico. Am J Trop Med Hyg 2016; 94: 1085–89. 26 UPMC Center for Health Security. Infectious disease cost calculator. 2015. http://www.idcostcalc.org/contents/about/cost-of-ID.html (accessed June 16, 2015). 27 Grimwood K, Lambert SB, Milne RJ. Rotavirus infections and vaccines. Pediatr Drugs 2010; 12: 235–56. 28 Rheingans RD, Antil L, Dreibelbis R, Podewils LJ, Bresee JS, Parashar UD. Economic costs of rotavirus gastroenteritis and cost-eff ectiveness of vaccination in developing countries. J Infect Dis 2009; 200 (suppl 1): S16–S27. 29 Lee BY, Bacon KM, Bottazzi ME, Hotez PJ. Global economic burden of Chagas disease: a computational simulation model. Lancet Infect Dis 2013; 13: 342–48. 30 Hampson K, Coudeville L, Lembo T, et al. Estimating the global burden of endemic canine rabies. PLoS Negl Trop Dis 2015; 9: e0003709. for any systematic analysis. These include, for example, a degradation of the quality of treatment for patients with and without dengue because of health-system congestion during a dengue outbreak, potential economic eff ects of dengue on tourism and travel, and comorbidities and complications associated with dengue virus infection. 7,23 We did not include persistent symptoms of dengue in our analysis. Some patients with dengue present persistent symptoms that might aff ect their ability to work, including profound fatigue, depression, and weight loss. Persistent symptoms have been acknowledged by WHO since 1997, 24 and have been identifi ed in empirical studies in Latin American and Asia. 25 Results from a study in Mexico suggest that accounting for persistent symptoms would increase estimates of the economic burden of dengue illness by about 13%. 25 Our estimates indicate that dengue illness imposes costs greater than other major infectious diseases with comparable data such as cholera ($3∙1 billion), 26 rotavirus gastroenteritis ($2 billion globally 27 and $0∙4 billion in developing countries), 28 Chagas ($7∙2 billion), 29 and canine rabies ($8∙6 billion). 30 The global cost of dengue is substantial. If control strategies could reduce dengue appreciably, billions of dollars could be saved globally each year. With the availability of new and promising technologies to control dengue, policy makers and donors need reliable economic data to assist in their decisions to adopt these new approaches. 7 Contributors EAU and YAH prepared the data and table. JDS did statistical analyses of the numbers of dengue cases. All authors conceived and designed the analyses and contributed to the analysis, development, writing, reviewing, editing, and approval of the fi nal version of the manuscript. Declaration of interests We declare no competing interests. Acknowledgments Editorial assistance with the preparation of an early version of the manuscript was provided by a professional medical writer, Simon Lancaster (inScience Communications, Springer Healthcare) funded by Sanofi Pasteur. We thank Clare Hurley for assistance with revisions. References 1 Bhatt S, Gething PW, Brady OJ, et al. The global distribution and burden of dengue. Nature 2013; 496: 504–07. 2 Simmons CP, Farrar JJ, Nguyen VVC, Wills B. Current concepts: dengue. N Engl J Med 2012; 366: 1423–32. 3 Beatty ME, Beutels P, Meltzer MI, et al. Health economics of dengue: a systematic literature review and expert panel’s assessment. Am J Trop Med Hyg 2011; 84: 473–88. 4 Shepard DS, Coudeville L, Halasa YA, Zambrano B, Dayan GH. Economic impact of dengue illness in the Americas. Am J Trop Med Hyg 2011; 84: 200–07. 5 Shepard DS, Undurraga EA, Halasa YA. Economic and disease burden of dengue in Southeast Asia. PLoS Negl Trop Dis 2013; 7: e2055. 6 Brady OJ, Gething PW, Bhatt S, et al. Refi ning the global spatial limits of dengue virus transmission by evidence-based consensus. PLoS Negl Trop Dis 2012; 6: e1760. 7 Shepard DS, Undurraga EA, Betancourt-Cravioto M, et al. Approaches to refi ning estimates of global burden and economics of dengue. PLoS Negl Trop Dis 2014; 8: e3306. 8 World Health Organization. The global burden of disease: 2004 update. 2008. http://www.who.int/healthinfo/global_burden_ disease/GBD_report_2004update_full.pdf (accessed April 4, 2016).
Please help me out with this assignment, case study 3. You can use the articles and graphs on “case study 3“ file to finish this assignment. Thanks.
Like The Atlantic ? Subscribe to The Atlantic Daily , our free weekday email newsletter. Email S IG N U P H is to ry  i s  fi lt h y w it h  s to rie s o f p est c o n tr o l g o n e t e rrib ly , t e rrib ly  w ro n g. C on sid er, f o r e x am ple , t h e i n fa m ou s t a le  o f h ow  t h e m on go ose  g o t t o  t h e H aw aiia n Is la n ds. T he s le ek  c a rn iv o re  w as i m porte d  i n  t h e 1 880s a s p art o f a  p la n  b y t h e G en etic a lly M od ifi ed M osq u it o es: W hat C ou ld P o ssib ly G o W ro n g? The Zika virus could open the door for a new era of gene‑tweaking for pest control and disease prevention. AD RIE N NE L A FR A N CE APR 2 6 , 2 0 16 | T EC H NO LO GY James Gathany/ CDC / Reuters su gar i n dustr y  t o  s u b d u e t h e r a ts  t h at w ou ld n’t  s to p gn aw in g  th ro u gh  s ta lk s o f s u gar ca n e. M on go ose  d o e n jo y a  t a sty  r a t s u pp er, w hen  t h e o p p ortu n it y  p re se n ts  i t s e lf , b u t th ere  w as a  p ro b le m : R ats  a re  a ctiv e  a t n igh t, w hile  m on go ose  a re  a ctiv e  d urin g t h e day . S o i n ste a d  o f d ecim atin g  th e r a t p opu la tio n , t h e m on go ose  c a m e t o  H aw aii a n d fe a ste d  o n  n ativ e  b ir d s a n d t h eir  e gg s. T he r a t s c o u rg e c o n tin u ed  u n ab ate d . A ustr a lia  i m ple m en te d  a  s im ila rly  i ll- c o n ce iv e d  p la n  w hen  i t  i n tr o d u ce d  p ois o n ou s to ad s t o  i t s  s u gar-c a n e fi eld s i n  t h e 1 930s a s a  w ay  t o  c o n tr o l c ro p -d am ag in g beetle s. T he t o ad s t h riv e d  a n d w re a k ed  h avo c o n  n ativ e  s p ecie s, w hile  t h e b eetle s co n tin u ed  c h om pin g  aw ay  o n  t h e r o ots  a n d l e ave s o f s u gar c a n e, j u st a s t h ey h ad b efo re . T od ay , t h e o u tc o m e o f t h ese  a n d  sim ila r p est- c o n tr o l e x p erim en ts  r e m ain  p ara b le s fo r t h e f o lly  o f h um an  i n te rv e n tio n  i n to  c o m ple x  e co sy ste m s. P eo ple  h ave  s in ce b eco m e b ette r p rim ed  t o  s to p a n d  a sk , “ w hat i f ? ”  b efo re  a tte m ptin g a n en vir o n m en ta l r e sp on se  t h at c a n ’t  b e u n don e. B ut, “ w hat i f ”  i s  n eve r a n  e a sy q u estio n  t o  a n sw er. *  *  * T od ay , s c ie n tis ts  d on’t  n eed  m on go ose  o r t o ad s f o r p est c o n tr o l.  I n  s o m e c a se s, th ey c a n  j u st t w ea k  t h e g en es o f t h e a n im al o r i n se ct t h ey ’r e  t r y in g  to  v a n qu is h . T here ’s  g o od  e vid en ce  t o  s u pp ort t h e i d ea  t h at g en etic  m od ifi ca tio n  o f t h e  A ed es a eg yp ti  m osq u it o , f o r e x am ple , c o u ld  h elp  d ra m atic a lly  r e d u ce  i t s  p opu la tio n . A ed es a eg yp ti  i s  t h e m ain  v e cto r o f t h e Z ik a v ir u s, a  m osq u it o -b orn e i lln ess t h at h as p u blic -h ea lt h  o ffic ia ls  a ro u n d t h e w orld  o n  e d ge. I n  B ra zil,  h un dre d s o f b ab ie s b orn to  Z ik a-in fe cte d  m oth ers  h ave  s u ff ere d  s e ve re  b ir th  d efe cts  s in ce  l a st y e a r. P ublic – h ea lt h  o ffic ia ls , w ho a re  c a llin g  Zik a a  gl ob al e m erg en cy , e stim ate  t h at n um ber w ill c lim b w ell i n to  t h e t h ou sa n ds i n  B ra zil a lo n e. I n  t h e U nit e d  S ta te s a n d e ls e w here , a s m osq u it o  s e a so n  r a m ps u p, p eo ple  a re  b ra cin g  fo r a d d it io n al o u tb re a k s. At t h e s a m e t im e, i n  a  s m all F lo rid a c o m mun it y  n ea r K ey W est, t h e F ood  a n d D ru g A dm in is tr a tio n  i s  a cce p tin g  pu blic  c o m men ts  o n   a p ro p osa l  f r o m  t h e b io te ch n olo gy fi rm  O xit e c t o  i n tr o d u ce  g en etic a lly  m od ifi ed   A ed es a eg yp ti  m ale s i n to  t h e l o ca l m osq u it o  p opu la tio n . I f O xit e c i s  s u cce ssfu l,  i t s  t e ch n olo gy  c o u ld  h elp  w ip e o u t A ed es a eg yp ti  i n  t h e r e gi on — an d p ro te ct p eo ple  f r o m  Z ik a t r a n sm is sio n  t h ere . O xit e c’s  p la n  i s  t o  i n je ct m osq u it o  e gg s w it h  D NA t h at c o n ta in s l e th al g en es, t h en re le a se  t h e g en etic a lly  m od ifi ed  m ale s f r o m  t h at b atc h  o f e gg s s o  t h ey c a n  m ate w it h  w ild  f e m ale s. ( M ale s d on’t  b it e ; s o  r e le a sin g  on ly  m ale s i s  a  w ay  t o  m ak e s u re th e r e le a se  o f t h ese  i n se cts  d oesn ’t  c o n tr ib u te  t o  t h e s p re a d  o f d is e a se .)  T he off sp rin g  of t h ese  l a b -tw ea k ed  m ale s a n d w ild  f e m ale s, h av in g  in herit e d  t h e a lt e re d D NA, c a n not s u rv iv e  t o  a d ult h ood . I f a ll g o es a s p la n ned , t h e m osq u it o  p opu la tio n sh ou ld  s h rin k a s a  r e su lt . T here ’s  a lr e a d y g o od  e v id en ce  t h at s h ow s O xit e c’s a p pro ach  c a n  w ork . F ie ld  t e sts  i n  P ir a cic a b a, B ra zil,  r e su lt e d  i n  a n  8 2 p erc e n t declin e t o  t h e m osq u it o  p opu la tio n  o ve r a n  e igh t- m on th  p erio d ,  O xit e c s a ys . A nd t h ere ’s  a  c o m pellin g  need  f o r t r y in g  to  c o n tr o l t h e m osq u it o  p opu la tio n  t h is w ay .  A ed es a eg yp ti  d on’t  j u st s p re a d  Z ik a, b u t a ls o  d en gu e f e ve r, y e llo w  f e ve r, a n d ch ik u n gu nya  v ir u s. “ A bou t 4 0 p erc e n t o f t h e gl ob al p opu la tio n  i s  a t r is k  [ f r o m ] t h is s p ecie s,”  s a id  A ndre w  M cK em ey, a n  e n to m olo gi st a n d t h e h ea d  o f fi eld  o p era tio n s fo r O xit e c. “ It’s  k in d o f t h e r a t o f t h e m osq u it o  w orld .” “ It i s i g n ora n ce , d is tr u st, f e a r o f t h e u n kn own , f e a r o f p rio r e ff orts t o use bio lo gy t o c o m bat p ests w hic h w en t so u r.” B esid es a ll t h at, e x is tin g  m osq u it o  c o n tr o ls  c le a rly  a re n ’t  e n ou gh —esp ecia lly  i n  t h e U nit e d  S ta te s, w here   th e fi gh t  o ve r s ta te  a n d f e d era l Z ik a f u n din g  has d evo lv e d  i n to p etty  p olit ic k in g,  w it h  R ep u blic a n s  b lo ck in g  em erg en cy  f u n din g  t o  fi gh t t h e d is e a se . “ M y o pin io n  o n  h ow  w e s h ou ld  p ro ce ed  i s  w e s h ou ld  a ggr essiv e ly  p u rs u e A ed es a eg yp ti  c o n tr o l— bu t w e h ave n ’t  s ta rte d  t h at y e t, a n d I ’m  n ot s u re  t h ere ’s  b een th e p olit ic a l w ill t o  d o i t ,”  s a id  P ete r H ote z, t h e d ea n  o f t h e N atio n al S ch ool o f Tro pic a l M ed ic in e a t B ay lo r C olle g e o f M ed ic in e. “ It’s  v e ry  l a b or i n te n siv e . I t r e q u ir e s g ettin g  rid  o f s ta n din g  bod ie s o f w ate r, p u ttin g  up w in dow  s c re en s, a n d doin g  hou se -to -h ou se  i n se ctic id al s p ra y .”  T he c o ord in ate d  e ff ort t h at’s  n ece ssa ry , H ote z s a ys, g o es b eyo n d a n yth in g t h e U .S.  h as e ve r d on e t o  c o n tr o l m osq u it o es i n t h e p ast. A s t e m pera tu re s w arm  a n d m osq u it o es e m erg e, i t  m ay  a lr e a d y b e t o o l a te f o r a t- r is k  c it ie s i n  t h e s ta te s t o  t a k e t h e p re ca u tio n s H ote z d esc rib es. W hic h  i s  p art o f w hy t h e p ro m is e  o f g en etic a lly  m od ifi ed  m osq u it o es i s  s o  a p p ea lin g t o  t h ose  w ho su pp ort t h e i d ea . B ut t h e q u estio n  o f g en etic  m od ifi ca tio n  r e m ain s f r a u gh t— in  p art b eca u se  o f le gi tim ate  s c ie n tifi c c o n ce rn s, b u t l a rg ely  b eca u se  o f m is in fo rm atio n  a n d c u lt u ra l re sis ta n ce  t o  g en etic  m od ifi ca tio n  m ore  b ro ad ly .  A  p oll  c o n du cte d  b y t h e A nnen berg  Public  P olic y  C en te r i n  F eb ru ary  f o u n d m ore  t h an  o n e-th ir d  o f A m eric a n s b elie ve d  g en etic a lly  m od ifi ed  m osq u it o es w ere  t o  b la m e f o r t h e s p re a d o f Z ik a. ( T hey ’r e  n ot.) O th ers  h ea r “ g en etic  m od ifi ca tio n” a n d t h ey t h in k  Ju ra ss ic P a rk ; o r t h ey b elie ve  t h at j u st b eca u se  s o m eth in g  is  n atu ra l,  i t  i s  s o m eh ow  b ette r. “ T he p u blic  f e a rs  g en etic  e n gi nee rin g.  N ea rly  a ll p olit ic ia n s d on’t  u n ders ta n d i t ,” s a id  A rth ur C ap la n , t h e f o u n din g  dir e cto r o f t h e D iv is io n  o f M ed ic a l E th ic s a t N YU Sch ool o f M ed ic in e. “ I d on’t  t h in k t h e i s su e i s  e co n om ic . I t i s  i gn ora n ce , d is tr u st, f e a r o f t h e u n kn ow n, f e a r o f p rio r e ff orts  t o  u se  b io lo gy  t o  c o m bat p ests  w hic h  w en t so u r.” “ C hem ic a l s p ra y  m ay  b e f a m ilia r, b u t i t  i s  a  b lu n derb u ss,”  C ap la n  a d ded .  “ O ld t e ch n olo gy  [ is ] h ard  t o  a im , o fte n  m is fi re s, a n d i s  h ard  t o  m ain ta in . G en etic e n gi neerin g  of n asty  i n se ct- p ests  i s  a  r ifl e— ve ry  p re cis e , l o w  r is k  t o  t h e u se r.” G en etic a lly  m od ifi ed  m osq u it o es m ay  b e “ o u r b est h op e”  f o r fi gh tin g Z ik a v ir u s, a cco rd in g  to  N in a F ed oro ff , a  m ole cu la r g en etic is t, a n d J o h n  B lo ck , t h e f o rm er U .S . se cre ta ry  o f a gr ic u lt u re , w ho  m ad e t h eir  c a se  i n   T he N ew  Y ork  T im es  e a rlie r t h is m on th . B eyo n d Z ik a, m osq u it o es p ose  s u ch  a n  e n orm ou s t h re at t o  h um an  h ea lt h , m an y s c ie n tis ts  h ave  a rgu ed , t h at t h e m ost s e n sib le  t h in g  to  d o w ou ld  b e t o  w ip e th em  o u t— eve n  i f  t h e e co lo gi ca l i m pact i s  u n kn ow ab le . “S eve ra l f a cts  a re  w orth  b ea rin g  in  m in d,”  t h e e vo lu tio n ary  b io lo gi st O li v a  J u dso n w ro te  i n  a n  o p -e d  f o r  T he N ew  Y ork  T im es  i n  2 003. “ F ir s t, o u r c u rre n t m eth od s o f m osq u it o  c o n tr o l a re  c ru de a n d k il l m ore  t h an  j u st m osq u it o es. A n e x tin ctio n  g en e at l e a st h as t h e b en efi t o f b ein g  pre cis e  a n d c le a n . S eco n d, t h ere ‘s  n oth in g s in is te r ab ou t e x tin ctio n ; s p ecie s g o  e x tin ct a ll t h e t im e. T he d is a p p ea ra n ce  o f a  f e w sp ecie s, w hile  a  p it y , d oes n ot b rin g  a w hole  e co sy ste m  c ra sh in g  dow n: W e’r e  n ot le ft w it h  a  w aste la n d e ve ry  t im e a  s p ecie s v a n is h es. R em ovin g  on e s p ecie s so m etim es c a u se s s h if ts  i n  t h e p opu la tio n s o f o th er s p ecie s— bu t d iff ere n t n eed  n ot m ea n  w ors e .” O xit e c, f o r i t s  p art, c la im s i t s  m eth od  o f m osq u it o  r e d u ctio n  w ou ld  b e m ore e ff ectiv e  t h an  t r a d it io n al i n se ctic id e a n yw ay , a n d w ou ld  c o st a b ou t t h e s a m e o r p ossib ly  l e ss. ( M cK em ey s a id  h e c o u ld n’t  o ff er a  p re cis e  c o st e stim ate  b eca u se  i t c o u ld  v a ry  d ep en din g  on  t h e l o ca tio n , i t s  h um an  a n d m osq u it o  p opu la tio n s, a n d oth er f a cto rs .) A technician from Oxitec inspects Aedes aegypti larvae in Campinas, Brazil. (Paulo Whitaker / Reuters) And y e t s o m e s c ie n tis ts  a re  s till r a is in g  qu estio n s a b ou t t h e p ro m is e  o f O xit e c’s t e ch n olo gy . “I’m  n ot s o  c o n ce rn ed  a b ou t t h e s a fe ty  i s su es. I  t h in k t h e b igg est i s su e n ow  i s : I s  i t g o in g  to  w ork ?”  H ote z s a id . “ It’s  o n ly  b een  t e ste d  a t a  s m all s c a le . I t’s  l o okin g pro m is in g,  t o  s e e a n  8 0 t o  9 0 p erc e n t r e d u ctio n  o f  A ed es a eg yp ti  m osq u it o es, b u t w e don’t  r e a lly  k n ow  w hat 8 0 t o  9 0 p erc e n t  m ea n s . I t c o u ld  b e t h at w e n eed  a  9 9- perc e n t r e d u ctio n  t o  g et a n  i m pact.” I n  o th er w ord s, i s  a n  8 0-p erc e n t r e d u ctio n  i n  t h e m osq u it o  p opu la tio n  e n ou gh  t o s to p t h e s p re a d  o f Z ik a? T he s h ort a n sw er i s : W e d on’t  k n ow . “T he ve ry t h in g w e’r e re le a sin g i s d esig n ed t o d is a p p ea r fr o m t h e en vir o n m en t w it h ou t a t r a ce .” T he l e ve l o f m osq u it o  s u ppre ssio n  t h at’s  n eed ed  t o  s to p d is e a se  t r a n sm is sio n d ep en ds o n  a  w id e v a rie ty  o f f a cto rs , i n clu d in g  th e m osq u it o  p opu la tio n , t h e h um an p opu la tio n , t h e a m ou n t o f d is e a se  a lr e a d y c ir c u la tin g,  a n d t h e p ro p ortio n  o f p eo ple p re vio u sly  i n fe cte d , a n d t h ere fo re  i m mun e. “O ur t e ch n olo gy  i s  a b ou t c o n tr o lli n g  th e m osq u it o  p opu la tio n , s o  w e d on’t  m ak e d ir e ct c la im s t h at w e’r e  c o n tr o llin g  dis e a se ,”  M cK em ey, t h e O xit e c s c ie n tis t, t o ld m e. “ Z ik a i s  s o  n ew  t h at w e d on’t  k n ow  e x actly  t h e p opu la tio n  d yn am ic  o f m osq u it o es a n d h um an s t h at’s  n eed ed  t o  s u sta in  a n  o u tb re a k . B ut i f  y o u  c a n  r e d u ce th e m osq u it o  p opu la tio n  s u ffic ie n tly , y o u  c a n  b re a k  t h at t r a n sm is sio n  c y cle .” T he o th er b ig  qu estio n  i s : H ow  s c a la b le  i s  O xit e c’s  a p pro ach ? G en etic a lly  m od ifi ed m osq u it o es m ay  h ave  b een  s u cce ssfu l a t r e d u cin g  th e  A ed es a eg yp ti  p opu la tio n  i n P ir a cic a b a, w here  O xit e c h as e x p an ded  i t s  t r ia ls  t o  c o ve r a n  a re a  t h at’s  h om e t o s o m e 6 0,0 00 p eo ple ; b u t w hat a b ou t m ore  d en se ly  p opu la te d  a re a s, o r t h e hun dre d s o f m ile s o f c it ie s a n d t o w ns a lo n g  th e G ulf  C oast? “ In  l e ss t h an  a  y e a r, f r o m  o n e f e m ale  A ed es a eg yp ti , y o u  c a n  w in d u p w it h  a  b illio n pro gen y,”  M cK em ey t o ld  m e. “ W hat I ’m  t r y in g  to  s a y  i s  t h e b io lo gy  o f i t  i s in cre d ib ly  s c a la b le , a n d u lt im ate ly  t h at’s  w hy t h ese  b u gs a re  s u ch  a  p ro b le m — beca u se  t h ey ’r e  s o  p ro lifi c. T his  k in d o f s c a la b ilit y  i s  n ot j u st t h at y o u  c o u ld t h eo re tic a lly  s c a le  u p t o  c o u n tr y  o r c o n tin en ta l s c a le ; i t  h as b een  d on e a n d i s  b ein g don e a gr ic u lt u ra lly .” T here  a re  s u cce ss s to rie s i n  a gr ic u lt u re — ste rilit y  b y g en etic  m od ifi ca tio n  h elp ed w ip e o u t  t h e N ew  W orld  s c re w worm  i n  t h e 1 960s, w hic h  o n ce  d eva sta te d  l i v e sto ck in  t h e U nit e d  S ta te s. Si m ila r m eth od s h ave  b een  u se d  t o  s u cce ssfu lly  fi gh t f r u it  fl ie s in  t h e U nit e d  S ta te s. S te rilit y  a s t h e e n d-r e su lt  o f g en etic  m od ifi ca tio n  h as o th er b en efi ts . F or o n e, i t  b asic a lly  m ak es a  s p ecie s b re ed  i t s e lf  o u t o f e x is te n ce — ra th er th an  i n tr o d u cin g  a n ew  k in d o f p est t h at c o n tin u es t o  p ass a lo n g  it s  a lt e re d  g en es f o r gen era tio n s. “ T here ’s  a n  i n here n t s a fe ty  a sp ect t o  w hat w e’r e  d oin g,”  M cK em ey sa id . “ T he v e ry  t h in g  w e’r e  r e le a sin g  is  d esign ed  t o  d is a p p ea r f r o m  t h e e n vir o n m en t w it h ou t a  t r a ce .” I n  c o n tr a st, o th er g en e-m od ifi ca tio n  m eth od s o f m osq u it o  c o n tr o l m ig h t a tte m pt t o a lt e r a  m osq u it o ’s  D NA s o  t h at i t ’s  n ot a s g o od  a t t r a n sm it tin g  a v ir u s; b u t i t  w ou ld s till b e a b le  t o  p ro d u ce  v ia b le  o ff sp rin g.  T hose  a p pro ach es a re , M cK em ey t o ld  m e, “ m ore  o f a  g en ie -o u t- o f-a -b ottle  s it u atio n .” “ T he p ote n tia l b en efi t o f t h at o th er a p pro ach  i s  y o u  m igh t n eed  t o  r e le a se  [ t h e g en e- alt e re d  m osq u it o es] l e ss o fte n , b u t t h e d ow nsid e i s  s o m eth in g  un fo re se en  h ap p en s, a n d i t ’s  o u t t h ere ,”  h e s a id . Som eth in g  un fo re se en  i s n ’t  o u t o f t h e q u estio n  f o r O xit e c’s  a p pro ach , e it h er, th ou gh . “Y o u c a n s ta rt t o fa n ta siz e a b ou t e ve ry p ossib le f a te o f t h at g en e, b u t i t ’s i m pos sib le t o t e st a ll o f t h at i n a l a b .” “ Y ou  n eed  t o  b e c o n ce rn ed  a b ou t w hat y o u  d on’t  k n ow ,”  s a id  R av i D urv a su la , a p ro fe ss o r o f M ed ic in e a n d I n fe ctio u s D is e a se s a t U niv e rs it y  o f N ew  M ex ic o  S ch ool o f M ed ic in e. “ O xit e c’s  [ a p pro ach ] i t s e lf  i s  fi n e, s c ie n tifi ca lly , b u t t h ere  a re  a lw ays th e w hat- if  s c e n ario s. W hat i f , f o r s o m e r e a so n , i t  d oesn ’t  w ork — an d r e ve rts  b ack  t o a  w ild -ty p e s ta te ?” W hat D urv a su la  m ea n s i s , w hat i f  t h e d esir e d  g en e m uta tio n  d oesn ’t  t a k e, a n d peo ple  e n d u p r e le a sin g  m ass q u an tit ie s o f n ew  m osq u it o es t h at e n d u p m ak in g t h e Z ik a p ro b le m  w ors e ? D urv a su la  c a lls  t h is  t h e “ m ost o b vio u s c o n ce rn ,”  b u t h e a ls o sa ys i t ’s  i m pro b ab le . “ It’s  a ls o  u n lik ely  t h at t h is  m uta n t i s  g o in g  to  s o m eh ow  m uta te  a g ain  a n d g iv e  y o u so m eth in g  un desir a b le ,”  h e a d ded . “ C erta in ly  t h ere  h ave  b een  s m all- s c a le  fi eld r e le a se s w here  i t ’s  b een  s ta b le , i t ’s  d on e w hat i t ’s  s u pp ose d  t o  d o, a n d t h ey d id n’t w in d u p w it h  b ir d -s iz e d  m osq u it o es o r s o m eth in g  els e  w eir d . O xit e c h as g o n e th ro u gh  a  l o t o f r ig o ro u s t e stin g,  b u t t h ese  w hat- if  s c e n ario s— on e c a n ’t  b e 1 00 perc e n t c e rta in  t h at t h is  i s  f o olp ro o f.” W hat i f , f o r e x am ple , t h e g en e m od ifi ca tio n  e n ds u p a lt e rin g  a m osq u it o ’s  b eh av io r — m ak in g  it  m ore  a ggr essiv e , o r c h an gi ng  it s  h ost p re fe re n ce . ( I n  t h e c a se  o f  A ed es a eg yp ti , w hic h  a lr e a d y p re fe rs  h um an s , a  c h an ge i n  h ost p re fe re n ce  m igh t n ot b e s o b ad .) O r w hat i f  t h e m osq u it o es e n d u p t r a n sfe rrin g  th eir  a lt e re d  g en es h oriz o n ta lly — to  o th er n on -ta rg et s p ecie s, r a th er t h an  j u st t o  t h eir  o w n o ff sp rin g? T his  i s  m ore  o f a p ro b le m  w it h  g en etic a lly  m od ifi ed  b acte ria , w hic h  h as a ls o  b een  p ro p ose d  t o  fi gh t Z ik a, b u t D urv a su la  s a ys u n pla n ned  h oriz o n ta l g en e t r a n sfe r i s  u n lik ely  t o  c re ate a n y i s su es a m on g  A ed es a eg yp ti  t h at a re  g en etic a lly  m od ifi ed  t o  b e s te rile . “ Y ou  c a n  s ta rt t o  f a n ta siz e  a b ou t e ve ry  p ossib le  f a te  o f t h at g en e, b u t i t ’s  i m possib le t o  t e st a ll o f t h at i n  a  l a b ,”  h e s a id . “ A nd  o n ce  y o u’v e  r e le a se d  a  t r a it  i n to  a p opu la tio n , t h ere  c a n not b e a  r e ca ll.  T his  i s  w hat s c a re s p eo ple . P eo ple  g et c re ep ed o u t b y t h ese  t h in gs.” That f e a r i s  s ta n din g  in  t h e w ay  o f e n gi neerin g  A ed es a eg yp ti  in to  “ w ell- d ese rv e d o b li v io n ,”  s a ys C ap la n , t h e b io eth ic is t f r o m  N YU . B ut f e a r m ay  a ls o  b e a  b oon  t o  t h e eff ort t o  g en etic a lly  m od if y  m osq u it o es. D esp it e  w id esp re a d  m is in fo rm atio n , a b ou t 4 3 p erc e n t o f t h ose  p olle d  i n  t h e Feb ru ary  A nnen berg  su rv e y s a id  t h ey b elie ve d  g en etic a lly  m od ifi ed  m osq u it o es co u ld  h elp  m in im iz e  t h e s p re a d  o f t h e d is e a se . A  f o llo w -u p p oll b y A nnen berg , i n M arc h , f o u n d 5 3 p erc e n t o f t h ose  s u rv e ye d  e it h er s tr o n gl y o r s o m ew hat f a vo re d re le a sin g  gen etic a lly  m od ifi ed  m osq u it o es t o  c o m bat Z ik a.  S eve ra l o th er p olls  h ave d em on str a te d  s im ila r p u blic  s u pp ort f o r t h e k in d o f a p pro ach  O xit e c i s  p ro p osin g i n F lo rid a. A noth er p oll,  c o n du cte d  b y P urd u e U niv e rs it y  a n d t h e A ss o cia te d  P re ss, fo u n d  “ o ve rw helm in g”  s u pp ort— am on g 7 8 p erc e n t o f t h ose  s u rv e ye d — fo r u sin g gen etic a lly  m od ifi ed  m osq u it o es i n  t h e fi gh t a g ain st Z ik a. “ Y ou  t a k e s o m eth in g  lik e Z ik a v ir u s,”  D urv a su la  s a id . “ T hese  d is e a se s t h at c a n em erg e i n  w eek s. B ab ie s a re  b ein g b orn  w it h  d efo rm it ie s. T here ’s  t h e t h ou gh t o f se x u al t r a n sm is sio n  o f a  v ir u s t h at p eo ple  b are ly  u n ders ta n d. T alk  a b ou t f e a r f a cto r. T hen  y o u  s a y , l e t’s  l o ok a t t h e t w o s id es o f i t ; w e h ave  s o m e f e a r a b ou t t h ese g en etic a lly  m od ifi ed  m osq u it o es, b u t w e’r e  t e rrifi ed  o f t h is  d is e a se  w hic h  c a n Genetically modified male Aedes aegypti mosquitoes at an Oxitec plant (Paulo Whitaker / Reuters) sp re a d  q u ic k ly — an d f o r w hic h  t h ere ’s  n o c u re  a n d t h e v a cc in e i s  s till b ein g deve lo p ed . I f y o u  w eigh  t h ese , t h at’s  w here  p eo ple  m igh t s a y  g en etic  m od ifi ca tio n m ay  b e t h e l e ss e r o f t w o e vils .” “ T hin k a b ou t h ow  p eo ple  c o n tr o l m osq u it o es n ow ,”  h e a d ded . “ D um pin g pestic id es o ve r h un dre d s o f s q u are  m ile s . .. d riv in g  th ro u gh  t h e c it y  w it h  c a n is te rs o n  m oto rb ik es, s p ra y in g  w illy -n illy . T hat’s  a n  i n cre d ib ly  t o xic  a p pro ach . A s p eo ple b ette r u n ders ta n d t h e s id e e ff ects  o f p estic id es, t h ey m ay  s a y , ‘ W ell,  t h is  o th er w ay , th ere ’s  n oth in g  to xic  a b ou t i t , a n d n o o n e’s  d yin g  fr o m  m osq u it o es t h at a re  s te rile .’ T he m ore  t h ese  o f t h ese  k in ds o f d is e a se s s h ow  u p — th e m ore  b ig,  b ig  o u tb re a k s aro u n d t h e w orld — I t h in k t h ere  w ill b e a  t im e w hen  p eo ple  s a y , ‘ W e n eed  t o  t r y s o m eth in g  new .’” A BO UT T H E A U TH O R AD RIE N NE L A FR A N CE is the editor of TheAtlantic.com. She was previously a senior editor and staff writer at The Atlantic .  Twitter  Facebook
Please help me out with this assignment, case study 3. You can use the articles and graphs on “case study 3“ file to finish this assignment. Thanks.
Part 1: Vector Capacity (3 points) d. Simulating conditions for the year 2050, the model predicts a vector capacity of ___________. (1 pt) e. If our model took mosquito and dengue thermal limits into account, how do you think graph “1a) Vector Capacity by Temperature” would look if we predicted VC for even greater temperatures? (2 pts) Part 2: Modeling an outbr eak (9 points) a. For the simple outbreak scenario (death rate = 0.0001), what proportion of the 1000 people in the town get the disease over the course of the year? This includes those who remain infectious at day 365 as well as those who have recovered. ____________ (1 pt) b. Is the outbreak still going on at the end of the year? ( Yes / No ) (1 pt) c. As multiple serotypes of dengue are introduced into the population, the death rate of subsequent epidemics increases. How does this af fect the number of individuals who die over the course of an outbreak? (1pt) i. Linear increase ii. Linear decrease iii. No change iv . Increases to a threshold then declines d. At what death rate do the maximum number of deaths occur? ____________ (1 pt) HINT : Use your data points rather than the trendline to answer this question. e. How do you explain the result described in question (c & d)? HINT : Think about how dengue spreads through a population (4 pts) Your answer should be 150 – 200 words. f. At the maximum death rate used (i.e. all possible serotypes are present in the region) is the outbreak still going on at the end of the year? ( Yes / No ) (1 pt) Part 3: Pr eventing epidemics (8 points) a. Describe your two alternative strategies for preventing or mitigating dengue outbreaks and how you incorporated them in the model. Use reference to the readings where appropriate. NOTE : Slowing or stopping climate change is not an option for this response. Be sure and justify your use of the vector capacity or outbreak modeling approach. Your answer should be 250 – 300 words. (4 pts) b. Which strategy will be the most ef fective and why? Which strategy will be the most useful in future climate scenarios? Be sure and use your graphs to explain your answer as well as the background readings. Your answer should be 250 – 300 words. (4 points)
Please help me out with this assignment, case study 3. You can use the articles and graphs on “case study 3“ file to finish this assignment. Thanks.
Part 1: Vector Capacity (6 points) a. Decreasing incubation time corresponds to ( increasing / decreasing / no change in ) vector capacity . (1 pt) incr easing b. Increasing transmission rate leads to ( increasing / decreasing / no change in ) vector capacity . (1 pt) incr easing c. Increasing number of female mosquitoes per person leads to ( increasing / decreasing / no change in ) vector capacity . (1 pt) incr easing d. Simulating conditions for the year 2050, the model predicts a vector capacity of ___________. (1 pt) e. If our model took mosquito and dengue thermal limits into account, how do you think graph “1a) Vector Capacity by Temperature” would look if we predicted VC for even greater temperatures? (2 pts) Part 2: Modeling an outbr eak (9 points) a. For the simple outbreak scenario (death rate = 0.0001), what proportion of the 1000 people in the town get the disease over the course of the year? This includes those who remain infectious at day 365 as well as those who have recovered. ____________ (1 pt) b. Is the outbreak still going on at the end of the year? ( Yes / No ) (1 pt) c. As multiple serotypes of dengue are introduced into the population, the death rate of subsequent epidemics increases. How does this af fect the number of individuals who die over the course of an outbreak? (1pt) i. Linear increase ii. Linear decrease iii. No change iv . Increases to a threshold then declines d. At what death rate do the maximum number of deaths occur? ____________ (1 pt) HINT : Use your data points rather than the trendline to answer this question. e. How do you explain the result described in question (c & d)? HINT : Think about how dengue spreads through a population (4 pts) Your answer should be 150 – 200 words. f. At the maximum death rate used (i.e. all possible serotypes are present in the region) is the outbreak still going on at the end of the year? ( Yes / No ) (1 pt) Part 3: Pr eventing epidemics (8 points) a. Describe your two alternative strategies for preventing or mitigating dengue outbreaks and how you incorporated them in the model. Use reference to the readings where appropriate. NOTE : Slowing or stopping climate change is not an option for this response. Be sure and justify your use of the vector capacity or outbreak modeling approach. Your answer should be 250 – 300 words. (4 pts) b. Which strategy will be the most ef fective and why? Which strategy will be the most useful in future climate scenarios? Be sure and use your graphs to explain your answer as well as the background readings. Your answer should be 250 – 300 words. (4 points) Part 1d: Vector Capacity equals 8.0474

Writerbay.net

We’ve proficient writers who can handle both short and long papers, be they academic or non-academic papers, on topics ranging from soup to nuts (both literally and as the saying goes, if you know what we mean). We know how much you care about your grades and academic success. That's why we ensure the highest quality for your assignment. We're ready to help you even in the most critical situation. We're the perfect solution for all your writing needs.

Get a 15% discount on your order using the following coupon code SAVE15


Order a Similar Paper Order a Different Paper