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For millennia the Nile supplied Egypt with more water than needed. As the population grew and the economy expanded, demand on water increased accordingly. Here, we present a comprehensive analysis to reconstruct how total demand on water outstripped supply of the Nile water in the late 1970s, starting from a surplus of about 20 km3 per year in the 1960s leading to a deficit of about 40 km3 per year by the late 2010s. The gap is satisfied by import of virtual water. The role of economic growth in driving per capita demand on water is quantified based on detailed analysis of water use by agriculture and other sectors. We develop and test an empirical model of water demand in Egypt that relates demand on water to growth rates in the economy and population. Looking forward, we project that within this decade of the 2020 s, under nominal scenarios of population and economic growth, Egypt is likely to import more virtual water than the water supplied by the Nile, bringing into question the historical characterization of Egypt as "the gift of the Nile".
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Viral respiratory diseases (VRDs), such as influenza and COVID-19, are thought to spread faster during winter than during summer. It has been previously argued that cold and dry conditions are more conducive to the transmission of VRDs than warm and humid climates, although this relationship appears restricted to temperate regions and the causal relationship is not well understood. The severe acute respiratory syndrome coronavirus 2 causing COVID-19 has emerged as a serious global public health problem after the first COVID-19 reports in Wuhan, China, in late 2019. It is still unclear whether this novel respiratory disease will ultimately prove to be a seasonal endemic disease. Here, we suggest that air drying capacity (ADC; an atmospheric state variable that controls the fate/evolution of the virus-laden droplets) and ultraviolet radiation (UV) are probable environmental determinants in shaping the transmission of COVID-19 at the seasonal time scale. These variables, unlike temperature and humidity, provide a physically based framework consistent with the apparent seasonal variability in COVID-19 and prevalent across a broad range of climates (e.g., Germany and India). Since this disease is known to be influenced by the compounding effect of social, biological, and environmental determinants, this study does not claim that these environmental determinants exclusively shape the seasonality of COVID-19. However, we argue that ADC and UV play a significant role in COVID-19 dynamics at the seasonal scale. These findings could help guide the development of a sound adaptation strategy against the pandemic over the coming seasons.
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BACKGROUND: Rainfall patterns are one of the main drivers of dengue transmission as mosquitoes require standing water to reproduce. However, excess rainfall can be disruptive to the Aedes reproductive cycle by "flushing out" aquatic stages from breeding sites. We developed models to predict the occurrence of such "flushing" events from rainfall data and to evaluate the effect of flushing on dengue outbreak risk in Singapore between 2000 and 2016. METHODS: We used machine learning and regression models to predict days with "flushing" in the dataset based on entomological and corresponding rainfall observations collected in Singapore. We used a distributed lag nonlinear logistic regression model to estimate the association between the number of flushing events per week and the risk of a dengue outbreak. RESULTS: Days with flushing were identified through the developed logistic regression model based on entomological data (test set accuracy = 92%). Predictions were based upon the aggregate number of thresholds indicating unusually rainy conditions over multiple weeks. We observed a statistically significant reduction in dengue outbreak risk one to six weeks after flushing events occurred. For weeks with five or more flushing events, compared with weeks with no flushing events, the risk of a dengue outbreak in the subsequent weeks was reduced by 16% to 70%. CONCLUSIONS: We have developed a high accuracy predictive model associating temporal rainfall patterns with flushing conditions. Using predicted flushing events, we have demonstrated a statistically significant reduction in dengue outbreak risk following flushing, with the time lag well aligned with time of mosquito development from larvae and infection transmission. Vector control programs should consider the effects of hydrological conditions in endemic areas on dengue transmission.
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Aedes/fisiologia , Dengue/epidemiologia , Surtos de Doenças , Modelos Estatísticos , Controle de Mosquitos , Mosquitos Vetores/fisiologia , Animais , Dengue/transmissão , Entomologia , Humanos , Chuva , Singapura/epidemiologiaRESUMO
BACKGROUND: Many large dams are constructed annually in Africa, with associated reservoirs that might exacerbate the risk of malaria in new villages built nearby. We aimed to investigate the heterogeneous risk of malaria around reservoirs related to the impact of wind direction on malaria transmission. METHODS: Between June 15, 2012, and April 22, 2015, we obtained field data on climate and hydrological conditions, and monitored Anopheles mosquito populations around the Koka reservoir in Ethiopia using in-situ weather stations, mosquito light traps, and larval dipping. The field data were used to calibrate a field-tested, spatially explicit mechanistic malaria transmission model, the Hydrology, Entomology, and Malaria Transmission Simulator (HYDREMATS), to investigate the effect of relative wind direction on malaria transmission and associated mechanisms. We combined our simulation results and observational data to assess the association between village location around a reservoir and risk of malaria. FINDINGS: HYDREMATS simulations showed that wind blowing from a village towards a reservoir increases the size of malaria vector populations, whereas wind blowing from a reservoir towards a village decreases the size of malaria vector populations, which was consistent with our field data. Larval mortality is low in locations with village-to-reservoir wind due to weak surface waves, and this wind direction creates conditions that enable mosquitoes to identify village locations more easily than in conditions caused by reservoir-to-village wind, which increases the size of malaria vector populations, and thus malaria transmission. Among the wind conditions investigated (0·5-5 m/s), the effect of CO2 attraction on the size of the Anopheles population was largest at wind speeds of 0·5 m/s and 1 m/s, decreasing with higher wind speed. At a wind speed of 5 m/s, the effect of CO2 attraction was negligible, whereas the effect of waves was strongest. The effect of advection on Anopheles population size was negligible at all wind speeds and wind directions. INTERPRETATION: The effect of wind on malaria transmission around reservoirs can be substantial. The transmission of malaria can be minimised if the location of villages situated near a reservoir is carefully considered. For areas in which the environmental conditions surrounding a resevoir are equal, villages should be located downwind of reservoirs to reduce the incidence of malaria, although further research will be required in locations where wind direction changes in different seasons. FUNDING: US National Science Foundation, and Cooperative Agreement between the Masdar Institute of Science and Technology, Abu Dhabi, UAE, and the Massachusetts Institute of Technology, Cambridge, MA, USA.
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Anopheles/fisiologia , Transmissão de Doença Infecciosa/prevenção & controle , Lagos , Malária/transmissão , Distribuição Animal , Animais , Etiópia , Geografia , Dinâmica Populacional , Risco , Abastecimento de Água , VentoRESUMO
North China Plain is the heartland of modern China. This fertile plain has experienced vast expansion of irrigated agriculture which cools surface temperature and moistens surface air, but boosts integrated measures of temperature and humidity, and hence enhances intensity of heatwaves. Here, we project based on an ensemble of high-resolution regional climate model simulations that climate change would add significantly to the anthropogenic effects of irrigation, increasing the risk from heatwaves in this region. Under the business-as-usual scenario of greenhouse gas emissions, North China Plain is likely to experience deadly heatwaves with wet-bulb temperature exceeding the threshold defining what Chinese farmers may tolerate while working outdoors. China is currently the largest contributor to the emissions of greenhouse gases, with potentially serious implications to its own population: continuation of the current pattern of global emissions may limit habitability in the most populous region, of the most populous country on Earth.
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BACKGROUND: Wind conditions, as well as other environmental conditions, are likely to influence malaria transmission through the behaviours of Anopheles mosquitoes, especially around water-resource reservoirs. Wind-induced waves in a reservoir impose mortality on aquatic-stage mosquitoes. Mosquitoes' host-seeking activity is also influenced by wind through dispersion of [Formula: see text]. However, no malaria transmission model exists to date that simulated those impacts of wind mechanistically. METHODS: A modelling framework for simulating the three important effects of wind on the behaviours of mosquito is developed: attraction of adult mosquitoes through dispersion of [Formula: see text] ([Formula: see text] attraction), advection of adult mosquitoes (advection), and aquatic-stage mortality due to wind-induced surface waves (waves). The framework was incorporated in a mechanistic malaria transmission simulator, HYDREMATS. The performance of the extended simulator was compared with the observed population dynamics of the Anopheles mosquitoes at a village adjacent to the Koka Reservoir in Ethiopia. RESULTS: The observed population dynamics of the Anopheles mosquitoes were reproduced with some reasonable accuracy in HYDREMATS that includes the representation of the wind effects. HYDREMATS without the wind model failed to do so. Offshore wind explained the increase in Anopheles population that cannot be expected from other environmental conditions alone. CONCLUSIONS: Around large water bodies such as reservoirs, the role of wind in the dynamics of Anopheles population, hence in malaria transmission, can be significant. Modelling the impacts of wind on the behaviours of Anopheles mosquitoes aids in reproducing the seasonality of malaria transmission and in estimation of the risk of malaria around reservoirs.
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Anopheles/fisiologia , Malária/transmissão , Modelos Biológicos , Mosquitos Vetores/fisiologia , Vento , Animais , Simulação por Computador , Dinâmica Populacional , Recursos HídricosRESUMO
Dengue is the most important human arboviral disease in Singapore. We classified residential areas into low-rise and high-rise housing and investigated the influence of urban drainage on the distribution of dengue incidence and outdoor breeding at neighborhood and country scales. In Geylang area (August 2014 to August 2015), dengue incidence was higher in a subarea of low-rise housing compared to high-rise one, averaging 26.7 (standard error, SE = 4.83) versus 2.43 (SE = 0.67) per 1,000 people. Outdoor breeding drains of Aedes aegypti have clustered in the low-rise housing subarea. The pupal density per population was higher in the low-rise blocks versus high-rise ones, 246 (SE = 69.08) and 35.4 (SE = 25.49) per 1,000 people, respectively. The density of urban drainage network in the low-rise blocks is double that in the high-rise ones, averaging 0.05 (SE = 0.0032) versus 0.025 (SE = 0.00245) per meter. Further, a holistic analysis at a country-scale has confirmed the role of urban hydrology in shaping dengue distribution in Singapore. Dengue incidence (2013-2015) is proportional to the fractions of the area (or population) of low-rise housing. The drainage density in low-rise housing is 4 times that corresponding estimate in high-rise areas, 2.59 and 0.68 per meter, respectively. Public housing in agglomerations of high-rise buildings could have a positive impact on dengue if this urban planning comes at the expense of low-rise housing. City planners in endemic regions should consider the density of drainage networks for both the prevention of flooding and the breeding of mosquitoes.
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New dam construction is known to exacerbate malaria transmission in Africa as the vectors of malaria-Anopheles mosquitoes-use bodies of water as breeding sites. Precise environmental mechanisms of how reservoirs exacerbate malaria transmission are yet to be identified. Understanding of these mechanisms should lead to a better assessment of the impacts of dam construction and to new prevention strategies. Combining extensive multiyear field surveys around the Koka Reservoir in Ethiopia and rigorous model development and simulation studies, environmental mechanisms of malaria transmission around the reservoir were examined. Most comprehensive and detailed malaria transmission model, Hydrology, Entomology, and Malaria Transmission Simulator, was applied to a village adjacent to the reservoir. Significant contributions to the dynamics of malaria transmission are shaped by wind profile, marginal pools, temperature, and shoreline locations. Wind speed and wind direction influence Anopheles populations and malaria transmission during the major and secondary mosquito seasons. During the secondary mosquito season, a noticeable influence was also attributed to marginal pools. Temperature was found to play an important role, not so much in Anopheles population dynamics, but in malaria transmission dynamics. Change in shoreline locations drives malaria transmission dynamics, with closer shoreline locations to the village making malaria transmission more likely. Identified environmental mechanisms help in predicting malaria transmission seasons and in developing village relocation strategies upon dam construction to minimize the risk of malaria.
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The risk associated with any climate change impact reflects intensity of natural hazard and level of human vulnerability. Previous work has shown that a wet-bulb temperature of 35°C can be considered an upper limit on human survivability. On the basis of an ensemble of high-resolution climate change simulations, we project that extremes of wet-bulb temperature in South Asia are likely to approach and, in a few locations, exceed this critical threshold by the late 21st century under the business-as-usual scenario of future greenhouse gas emissions. The most intense hazard from extreme future heat waves is concentrated around densely populated agricultural regions of the Ganges and Indus river basins. Climate change, without mitigation, presents a serious and unique risk in South Asia, a region inhabited by about one-fifth of the global human population, due to an unprecedented combination of severe natural hazard and acute vulnerability.
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Clima , Temperatura Alta , Populações Vulneráveis , Agricultura , Ásia , Mudança Climática , Humanos , Modelos Teóricos , Densidade Demográfica , Pobreza , Análise Espaço-Temporal , TemperaturaRESUMO
BACKGROUND: Malaria transmission is complex, involving a range of hydroclimatological, biological, and environmental processes. The high degree of non-linearity in these processes makes it difficult to predict and intervene against malaria. This study seeks both to define a minimal number of malaria transmission determinants, and to provide a theoretical basis for sustainable environmental manipulation to prevent malaria transmission. METHODS: Using a field-tested mechanistic malaria model, HYDREMATS, a theoretical study was conducted under hypothetical conditions. Simulations were conducted with a range of hydroclimatological and environmental conditions: temperature (t), length of wet season (Twet), storm inter-arrival time (Tint), persistence of vector breeding pools (Ton), and distribution of houses from breeding pools and from each other (Xdist and Ydist, respectively). Based on the theoretical study, a malaria time scale, To, and a predictive theory of malaria transmission were introduced. The performance of the predictive theory was compared against the observational malaria transmission data in West Africa. Population density was used to estimate the scale that describes the spatial distribution of houses. RESULTS: The predictive theory shows a universality in malaria endemic conditions when plotted using two newly-introduced dimension-less parameters. The projected malaria transmission potential compared well with the observation data, and the apparent differences were discussed. The results illustrate the importance of spatial aspects in malaria transmission. CONCLUSIONS: The predictive theory is useful in measuring malaria transmission potential, and it can also provide guidelines on how to plan the layout of human habitats in order to prevent endemic malaria. Malaria-resistant villages can be designed by locating houses further than critical distances away from breeding pools or by removing pools within a critical distance from houses; the critical distance is described in the context of local climatology and hydrology.
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Meio Ambiente , Malária/transmissão , África Ocidental , Humanos , Modelos Teóricos , População RuralRESUMO
In dengue-endemic areas, transmission shows both a seasonal and interannual variability. To investigate how rainfall impacts dengue seasonality in Singapore, we carried out a longitudinal survey in the Geylang neighborhood from August 2014 to August 2015. The survey comprised of twice-weekly random inspections to outdoor breeding habitats and continuous monitoring for positive ones. In addition, observations of rainstorms were collected. Out of 6824 inspected habitats, 67 contained Aedes aegypti, 11 contained Aedes albopictus and 24 contained Culex spp. The main outdoors habitat of Aedes aegypti was storm drains (54/67). We found that 80% of breeding sites in drains (43/54) were lost after intense rainstorms related to the wet phase of the Northeast monsoon (NE) between November 2014 and early January 2015. Subsequently, 95% (41/43) of these flushed drains had dried out during the dry phase of the NE in late January-February 2015. A return in the outdoor breeding of Aedes aegypti was observed after the onset of Southwest monsoon (SW) between May and August 2015. There was also a reduction in productivity of breeding habitats for larvae and pupae after the onset of the NE. In wet equatorial regions like Singapore, rainfall varies with the monsoons. A monsoon-driven sequence of flushing and drying shapes the outdoor seasonal abundance of Aedes aegypti. This finding can be used to optimize vector control strategies and better understand dengue in the context of climate change.
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Aedes/fisiologia , Insetos Vetores/fisiologia , Animais , Cruzamento , Mudança Climática , Dengue/transmissão , Ecossistema , Estações do Ano , SingapuraRESUMO
BACKGROUND: One of the concerns for future malaria epidemiology is the elevated risks of malaria around an ever-increasing number of dam sites. Controlling larval populations around reservoirs behind dams by manipulating the water levels of reservoirs could be an effective and sustainable measure for suppressing malaria epidemics; however, the effectiveness of the water-level manipulation and the contributing mechanisms have been poorly studied. In this paper, we focus on how water recession may lead to larval stranding. METHODS: Larvae of An. albimanus were studied to assess their susceptibility to stranding under different conditions representing reservoir shoreline environments in an experimental tank (50 cm × 100 cm). The tank was initially seeded with 80 larvae uniformly, and the numbers of larvae stranded on land and remaining in water were counted (summed up to recovered larvae), following the recession of water. The vertical water drawdown rate and the proportion of stranded larvae to recovered larvae (p) were measured. Shoreline conditions tested were inclinations of shore slopes (2% and 4%) and surface types (smooth, vegetated, rough, ridged). RESULTS: For the 2% slopes, the proportions of stranded larvae (p) increased by about 0.002, 0.004, and 0.010 as the water drawdown rate increased by a centimeter per day on the smooth, rough, and vegetated surfaces, respectively. p for the 4% slopes were smaller than for the 2% slopes. Unlike other surface conditions, no significant correlation between p and the drawdown rate was observed on the ridged surface. CONCLUSIONS: Larger proportions of Anopheles larvae were stranded at higher water drawdown rates, on smaller reservoir slopes, and under rough or vegetated surface conditions. Three mechanisms of larval stranding were identified: falling behind shoreline recession; entrapment in small closed water bodies; and inhabitation in shallow areas. Depending on the local vectors of Anopheles mosquitoes, the conditions for their favorable breeding sites correspond to the conditions for large larval stranding. If these conditions are met, water-level manipulation could be an effective measure to control malaria along shorelines of reservoirs behind dams.
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Anopheles/fisiologia , Surtos de Doenças/prevenção & controle , Água Doce/parasitologia , Malária/epidemiologia , Malária/prevenção & controle , Controle de Mosquitos/métodos , Animais , Larva/fisiologia , Dinâmica Populacional , Abastecimento de ÁguaRESUMO
BACKGROUND: Climate change is expected to affect the distribution of environmental suitability for malaria transmission by altering temperature and rainfall patterns; however, the local and global impacts of climate change on malaria transmission are uncertain. OBJECTIVE: We assessed the effect of climate change on malaria transmission in West Africa. METHODS: We coupled a detailed mechanistic hydrology and entomology model with climate projections from general circulation models (GCMs) to predict changes in vectorial capacity, an indication of the risk of human malaria infections, resulting from changes in the availability of mosquito breeding sites and temperature-dependent development rates. Because there is strong disagreement in climate predictions from different GCMs, we focused on the GCM projections that produced the best and worst conditions for malaria transmission in each zone of the study area. RESULTS: Simulation-based estimates suggest that in the desert fringes of the Sahara, vectorial capacity would increase under the worst-case scenario, but not enough to sustain transmission. In the transitional zone of the Sahel, climate change is predicted to decrease vectorial capacity. In the wetter regions to the south, our estimates suggest an increase in vectorial capacity under all scenarios. However, because malaria is already highly endemic among human populations in these regions, we expect that changes in malaria incidence would be small. CONCLUSION: Our findings highlight the importance of rainfall in shaping the impact of climate change on malaria transmission in future climates. Even under the GCM predictions most conducive to malaria transmission, we do not expect to see a significant increase in malaria prevalence in this region.
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Mudança Climática , Malária/transmissão , Modelos Teóricos , África Ocidental/epidemiologia , Humanos , Malária/epidemiologia , ChuvaRESUMO
BACKGROUND: Individuals continuously exposed to malaria gradually acquire immunity that protects from severe disease and high levels of parasitization. Acquired immunity has been incorporated into numerous models of malaria transmission of varying levels of complexity (e.g. Bull World Health Organ 50:347, 1974; Am J Trop Med Hyg 75:19, 2006; Math Biosci 90:385-396, 1988). Most such models require prescribing inputs of mosquito biting rates or other entomological or epidemiological information. Here, we present a model with a novel structure that uses environmental controls of mosquito population dynamics to simulate the mosquito biting rates, malaria prevalence as well as variability in protective immunity of the population. METHODS: A simple model of acquired immunity to malaria is presented and tested within the framework of the Hydrology, Entomology and Malaria Transmission Simulator (HYDREMATS), a coupled hydrology and agent-based entomology model. The combined model uses environmental data including rainfall, temperature, and topography to simulate malaria prevalence and level of acquired immunity in the human population. The model is used to demonstrate the effect of acquired immunity on malaria prevalence in two Niger villages that are hydrologically and entomologically very different. Simulations are conducted for the year 2006 and compared to malaria prevalence observations collected from the two villages. RESULTS: Blood smear samples from children show no clear difference in malaria prevalence between the two villages despite pronounced differences in observed mosquito abundance. The similarity in prevalence is attributed to the moderating effect of acquired immunity, which depends on prior exposure to the parasite through infectious bites - and thus the hydrologically determined mosquito abundance. Modelling the level of acquired immunity can affect village vulnerability to climatic anomalies. CONCLUSIONS: The model presented has a novel structure constituting a mechanistic link between spatial and temporal environmental variability and village-scale malaria transmission. Incorporating acquired immunity into the model has allowed simulation of prevalence in the two villages, and isolation of the effects of acquired immunity in dampening the difference in prevalence between the two villages. Without these effects, the difference in prevalence between the two villages would have been significantly larger in response to the large differences in mosquito populations and the associated biting rates.
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Malária/imunologia , Malária/transmissão , Plasmodium/imunologia , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Animais , Criança , Pré-Escolar , Clima , Simulação por Computador , Culicidae/crescimento & desenvolvimento , Métodos Epidemiológicos , Feminino , Humanos , Lactente , Recém-Nascido , Malária/epidemiologia , Masculino , Pessoa de Meia-Idade , Modelos Estatísticos , Níger/epidemiologia , Prevalência , População Rural , Análise Espaço-Temporal , Adulto JovemRESUMO
BACKGROUND: Low levels of relative humidity are known to decrease the lifespan of mosquitoes. However, most current models of malaria transmission do not account for the effects of relative humidity on mosquito survival. In the Sahel, where relative humidity drops to levels <20% for several months of the year, we expect relative humidity to play a significant role in shaping the seasonal profile of mosquito populations. Here, we present a new formulation for Anopheles gambiae sensu lato (s.l.) mosquito survival as a function of temperature and relative humidity and investigate the effect of humidity on simulated mosquito populations. METHODS: Using existing observations on relationships between temperature, relative humidity and mosquito longevity, we developed a new equation for mosquito survival as a function of temperature and relative humidity. We collected simultaneous field observations on temperature, wind, relative humidity, and anopheline mosquito populations for two villages from the Sahel region of Africa, which are presented in this paper. We apply this equation to the environmental data and conduct numerical simulations of mosquito populations using the Hydrology, Entomology and Malaria Transmission Simulator (HYDREMATS). RESULTS: Relative humidity drops to levels that are uncomfortable for mosquitoes at the end of the rainy season. In one village, Banizoumbou, water pools dried up and interrupted mosquito breeding shortly after the end of the rainy season. In this case, relative humidity had little effect on the mosquito population. However, in the other village, Zindarou, the relatively shallow water table led to water pools that persisted several months beyond the end of the rainy season. In this case, the decrease in mosquito survival due to relative humidity improved the model's ability to reproduce the seasonal pattern of observed mosquito abundance. CONCLUSIONS: We proposed a new equation to describe Anopheles gambiae s.l. mosquito survival as a function of temperature and relative humidity. We demonstrated that relative humidity can play a significant role in mosquito population and malaria transmission dynamics. Future modeling work should account for these effects of relative humidity.
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Anopheles/fisiologia , Entomologia/métodos , África , Animais , Anopheles/crescimento & desenvolvimento , Umidade , Modelos Teóricos , Dinâmica Populacional , Análise de Sobrevida , TemperaturaRESUMO
BACKGROUND: Early warnings of malaria transmission allow health officials to better prepare for future epidemics. Monitoring rainfall is recognized as an important part of malaria early warning systems. The Hydrology, Entomology and Malaria Simulator (HYDREMATS) is a mechanistic model that relates rainfall to malaria transmission, and could be used to provide early warnings of malaria epidemics. METHODS: HYDREMATS is used to make predictions of mosquito populations and vectorial capacity for 2005, 2006, and 2007 in Banizoumbou village in western Niger. HYDREMATS is forced by observed rainfall, followed by a rainfall prediction based on the seasonal mean rainfall for a period two or four weeks into the future. RESULTS: Predictions made using this method provided reasonable estimates of mosquito populations and vectorial capacity, two to four weeks in advance. The predictions were significantly improved compared to those made when HYDREMATS was forced with seasonal mean rainfall alone. CONCLUSIONS: HYDREMATS can be used to make reasonable predictions of mosquito populations and vectorial capacity, and provide early warnings of the potential for malaria epidemics in Africa.
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Métodos Epidemiológicos , Malária/epidemiologia , Malária/transmissão , Animais , Simulação por Computador , Culicidae/crescimento & desenvolvimento , Humanos , Níger/epidemiologia , Chuva , População RuralRESUMO
BACKGROUND: Malaria transmission models commonly incorporate spatial environmental and climate variability for making regional predictions of disease risk. However, a mismatch of these models' typical spatial resolutions and the characteristic scale of malaria vector population dynamics may confound disease risk predictions in areas of high spatial hydrological variability such as the Sahel region of Africa. METHODS: Field observations spanning two years from two Niger villages are compared. The two villages are separated by only 30 km but exhibit a ten-fold difference in anopheles mosquito density. These two villages would be covered by a single grid cell in many malaria models, yet their entomological activity differs greatly. Environmental conditions and associated entomological activity are simulated at high spatial- and temporal resolution using a mechanistic approach that couples a distributed hydrology scheme and an entomological model. Model results are compared to regular field observations of Anopheles gambiae sensu lato mosquito populations and local hydrology. The model resolves the formation and persistence of individual pools that facilitate mosquito breeding and predicts spatio-temporal mosquito population variability at high resolution using an agent-based modeling approach. RESULTS: Observations of soil moisture, pool size, and pool persistence are reproduced by the model. The resulting breeding of mosquitoes in the simulated pools yields time-integrated seasonal mosquito population dynamics that closely follow observations from captured mosquito abundance. Interannual difference in mosquito abundance is simulated, and the inter-village difference in mosquito population is reproduced for two years of observations. These modeling results emulate the known focal nature of malaria in Niger Sahel villages. CONCLUSION: Hydrological variability must be represented at high spatial and temporal resolution to achieve accurate predictive ability of malaria risk at the village scale, which can then be integrated appropriately to regional spatial scales and seasonal temporal scales. These results have important implications for models seeking to link the impacts of climate change and climate variability to malaria transmission. The highly focal nature of malaria in the Sahel makes detailed representation necessary to evaluate village-level risks associated with hydrology-related vector population variability.
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Anopheles/crescimento & desenvolvimento , Malária/transmissão , Animais , Simulação por Computador , Geografia , Humanos , Modelos Estatísticos , Níger , Medição de Risco/métodos , População RuralRESUMO
Climate affects malaria transmission through a complex network of causative pathways. We seek to evaluate the impact of hypothetical climate change scenarios on malaria transmission in the Sahel by using a novel mechanistic, high spatial- and temporal-resolution coupled hydrology and agent-based entomology model. The hydrology model component resolves individual precipitation events and individual breeding pools. The impact of future potential climate shifts on the representative Sahel village of Banizoumbou, Niger, is estimated by forcing the model of Banizoumbou environment with meteorological data from two locations along the north-south climatological gradient observed in the Sahel--both for warmer, drier scenarios from the north and cooler, wetter scenarios from the south. These shifts in climate represent hypothetical but historically realistic climate change scenarios. For Banizoumbou climatic conditions (latitude 13.54 N), a shift toward cooler, wetter conditions may dramatically increase mosquito abundance; however, our modeling results indicate that the increased malaria transmissibility is not simply proportional to the precipitation increase. The cooler, wetter conditions increase the length of the sporogonic cycle, dampening a large vectorial capacity increase otherwise brought about by increased mosquito survival and greater overall abundance. Furthermore, simulations varying rainfall event frequency demonstrate the importance of precipitation patterns, rather than simply average or time-integrated precipitation, as a controlling factor of these dynamics. Modeling results suggest that in addition to changes in temperature and total precipitation, changes in rainfall patterns are very important to predict changes in disease susceptibility resulting from climate shifts. The combined effect of these climate-shift-induced perturbations can be represented with the aid of a detailed mechanistic model.