Satellite-derived NDVI, LST, and climatic factors driving the distribution and abundance of <i>Anopheles</i>
 mosquitoes in a former malarious area in northwest Argentina

Juri, María Julia Dantur; Estallo, Elizabet Lilia; Almirón, Walter Ricardo; Santana, Mirta; Sartor, Paolo; Lamfri, Mario; Zaidenberg, Mario

doi:10.1111/jvec.12130

Cited by 22 publications

(16 citation statements)

References 27 publications

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“…For temperatures above 28°C, we observe positive relationship between day LST and malaria mortality with lag effect after two months. In Argentina [ 37 ], LST was shown to be the most important driver of malaria vector abundance however this study did not consider the lagged effect of LST. It has been shown that in hot weather, an increase in temperature in certain ranges results in rapid development of the malaria vectors and thus expected subsequent increase in mortality [ 34 ].…”

Section: Discussionmentioning

confidence: 99%

Remotely Sensed Environmental Conditions and Malaria Mortality in Three Malaria Endemic Regions in Western Kenya

2016

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BackgroundMalaria is an important cause of morbidity and mortality in malaria endemic countries. The malaria mosquito vectors depend on environmental conditions, such as temperature and rainfall, for reproduction and survival. To investigate the potential for weather driven early warning systems to prevent disease occurrence, the disease relationship to weather conditions need to be carefully investigated. Where meteorological observations are scarce, satellite derived products provide new opportunities to study the disease patterns depending on remotely sensed variables. In this study, we explored the lagged association of Normalized Difference Vegetation Index (NVDI), day Land Surface Temperature (LST) and precipitation on malaria mortality in three areas in Western Kenya.Methodology and FindingsThe lagged effect of each environmental variable on weekly malaria mortality was modeled using a Distributed Lag Non Linear Modeling approach. For each variable we constructed a natural spline basis with 3 degrees of freedom for both the lag dimension and the variable. Lag periods up to 12 weeks were considered. The effect of day LST varied between the areas with longer lags. In all the three areas, malaria mortality was associated with precipitation. The risk increased with increasing weekly total precipitation above 20 mm and peaking at 80 mm. The NDVI threshold for increased mortality risk was between 0.3 and 0.4 at shorter lags.ConclusionThis study identified lag patterns and association of remote- sensing environmental factors and malaria mortality in three malaria endemic regions in Western Kenya. Our results show that rainfall has the most consistent predictive pattern to malaria transmission in the endemic study area. Results highlight a potential for development of locally based early warning forecasts that could potentially reduce the disease burden by enabling timely control actions.

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Section: Discussionmentioning

confidence: 99%

Remotely Sensed Environmental Conditions and Malaria Mortality in Three Malaria Endemic Regions in Western Kenya

2016

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“…Annual cumulative precipitation is about 1100 mm, with a dry season from June to October with a monthly average rainfall of 30 mm, contrasting with the wet season from November to May with a monthly average rainfall reaching 160 mm [43]. It is possible to differentiate three seasons: one warm and dry, which corresponds to Spring (September-December), one warm and rainy, which corresponds to Summer (January-April), and one that is cold and humid which corresponds to Autumn and Winter (May-August) [17]. The city is crossed by the Tartagal River, and its urban area covers approximately 15 km 2 [43].…”

Section: Methodsmentioning

confidence: 99%

“…argytarsis and An. strodei are also found, together with other less abundant Anophelines [17]. Previous studies show that in the southern area of the subtropical mountainous rain forests in northwestern Argentina, the relative humidity is the major determinant of the abundance of An.…”

Section: Introductionmentioning

confidence: 99%

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Climate drivers of malaria at its southern fringe in the Americas

et al. 2019

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In this work we analyze potential environmental drivers of malaria cases in Northwestern Argentina. We inspect causal links between malaria and climatic variables by means of the convergent cross mapping technique, which provides a causality criterion from the theory of dynamic systems. Analysis is based on 12 years of weekly malaria P. vivax cases in Tartagal, Salta, Argentina—at the southern fringe of malaria incidence in the Americas—together with humidity and temperature time-series spanning the same period. Our results show that there are causal links between malaria cases and both maximum temperature, with a delay of five weeks, and minimum temperature, with delays of zero and twenty two weeks. Humidity is also a driver of malaria cases, with thirteen weeks delay between cause and effect. Furthermore we also determined the sign and strength of the effects. Temperature has always a positive non-linear effect on cases, with maximum temperature effects more pronounced above 25°C and minimum above 17°C, while effects of humidity are more intricate: maximum humidity above 85% has a negative effect, whereas minimum humidity has a positive effect on cases. These results might be signaling processes operating at short (below 5 weeks) and long (over 12 weeks) time delays, corresponding to effects related to parasite cycle and mosquito population dynamics respectively. The non-linearities found for the strength of the effect of temperature on malaria cases make warmer areas more prone to higher increases in the disease incidence. Moreover, our results indicate that an increase of extreme weather events could enhance the risks of malaria spreading and re-emergence beyond the current distribution. Both situations, warmer climate and increase of extreme events, will be remarkably increased by the end of the century in this hot spot of climate change.

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“…Climatic information was not included, owing to the coarse spatial resolution of such data sets, which would not permit fine-grained predictions. Regardless, rainfall is indeed reflected in the NDVI data via vegetational responses and consequently increased or decreased photosynthetic mass [ 28 ].…”

Section: Methodsmentioning

confidence: 99%

Potential distribution of mosquito vector species in a primary malaria endemic region of Colombia

et al. 2017

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Rapid transformation of natural ecosystems changes ecological conditions for important human disease vector species; therefore, an essential task is to identify and understand the variables that shape distributions of these species to optimize efforts toward control and mitigation. Ecological niche modeling was used to estimate the potential distribution and to assess hypotheses of niche similarity among the three main malaria vector species in northern Colombia: Anopheles nuneztovari, An. albimanus, and An. darlingi. Georeferenced point collection data and remotely sensed, fine-resolution satellite imagery were integrated across the Urabá –Bajo Cauca–Alto Sinú malaria endemic area using a maximum entropy algorithm. Results showed that An. nuneztovari has the widest geographic distribution, occupying almost the entire study region; this niche breadth is probably related to the ability of this species to colonize both, natural and disturbed environments. The model for An. darlingi showed that most suitable localities for this species in Bajo Cauca were along the Cauca and Nechí river. The riparian ecosystems in this region and the potential for rapid adaptation by this species to novel environments, may favor the establishment of populations of this species. Apparently, the three main Colombian Anopheles vector species in this endemic area do not occupy environments either with high seasonality, or with low seasonality and high NDVI values. Estimated overlap in geographic space between An. nuneztovari and An. albimanus indicated broad spatial and environmental similarity between these species. An. nuneztovari has a broader niche and potential distribution. Dispersal ability of these species and their ability to occupy diverse environmental situations may facilitate sympatry across many environmental and geographic contexts. These model results may be useful for the design and implementation of malaria species-specific vector control interventions optimized for this important malaria region.

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Satellite-derived NDVI, LST, and climatic factors driving the distribution and abundance of Anopheles mosquitoes in a former malarious area in northwest Argentina

Cited by 22 publications

References 27 publications

Remotely Sensed Environmental Conditions and Malaria Mortality in Three Malaria Endemic Regions in Western Kenya

Remotely Sensed Environmental Conditions and Malaria Mortality in Three Malaria Endemic Regions in Western Kenya

Climate drivers of malaria at its southern fringe in the Americas

Potential distribution of mosquito vector species in a primary malaria endemic region of Colombia

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