Ecophysiological and Climatological Effects on Distribution of Vector Species and Malaria Incidence in India

Abstract

The magnitude of regional malaria risk is dependent primarily on the dynamics and distribution of the vector species, which are determined mainly by climate conditions. A coupled model with ecophysiological and climatological factors was developed to estimate the spatiotemporal distribution of the five species of dominant malaria vectors in monsoon Asia. Here, we examined how the potential distribution obtained from the model could explain trends in malaria incidence observed in India, which has the highest number of confirmed cases of malaria in Asia. Most notably, there was a significant positive correlation between annual malaria incidences and the maximum generation number of vectors for each state (p < 0.001). Malaria incidence tended to increase exponentially as vector generation number increased. In addition, the interannual variation in observed regional malaria incidences was synchronized with that of the potential number of vector generations. The observed seasonal peak of malaria incidences corresponded closely to the simulated appearance period of vector species, except for intensively irrigated areas that experience anthropogenic impacts on hydrologic conditions. Simulated vector distributions effectively expressed spatial and temporal prevalence of malaria in India. This novel approach to modeling based on vector ecology is an effective method for assessing malaria risk.

Comparative assessment on the prevalence of mutations in the Plasmodium falciparum drug-resistant genes in two different ecotypes of Odisha state, India

“…et al, 2015), and therefore, malaria is considered as a local and focal disease (Conn et al, 2015; Dash et al, 2008; Rath, 2004). Several studies involving different ecological and climatic settings have provided evidence that malaria epidemiology can be significantly variable across small eco-climatic scales (Jambulingam et al, 1991; Kaga and Ohta, 2012; Schapira and Boutsika, 2012). For example, malaria epidemiological outcomes including distributional prevalence of mosquito vectors and malaria transmission were correlated with different ecotypes in Nigeria (Okwa et al, 2009), Kenya (Ingasia et al, 2015), Brazil (Rosa-Freitas et al, 2007), Southeast Asia (Seng et al, 1999) and India (Jambulingam et al, 1991; Ramar et al, 2014; Shukla et al, 2007; Singh et al, 2015).…”

A scoping review of importation and predictive models related to vector-borne diseases, pathogens, reservoirs, or vectors (1999–2016)

“…Search verification was conducted by manually searching the reference lists of ten randomly selected relevant papers for titles, which may be relevant to this scoping study [10,14,[17][18][19][20][21][22][23][24].…”

Converging Human and Malaria Vector Diagnostics with Data Management towards an Integrated Holistic One Health Approach

“…Although the major geographic distribution of malaria is assumed around the equator, it keeps being a latent global threat. Given the relation between malaria transmission and climate [ 2 ], the increase in global temperature is possibly causing tropical diseases and vectors to spread to higher altitudes in mountainous regions, and to higher latitudes that were previously spared. Furthermore, recent outbreaks of malaria in countries that had been malaria-free indicate the continuous threat of re-establishment of the disease in areas that were considered malaria-free [ 3 ].…”