Numerical Modeling of the Dynamics of Malaria Transmission in a Highly Endemic Region of India

Abstract

Using a dynamical model (VECTRI) for malaria transmission that accounts for the influence of population and climatic conditions, malaria transmission dynamics is investigated for a highly endemic region (state of Odisha) in India. The model is first calibrated over the region, and subsequently numerical simulations are carried out for the period 2000–2013. Using both model and observations we find that temperature, adult mosquito population, and infective biting rates have increased over this period, and the malaria vector abundance is higher during the summer monsoon season. Regionally, the intensity of malaria transmission is found to be higher in the north, central and southern districts of Odisha where the mosquito populations and the number of infective bites are more and mainly in the forest or mountainous ecotypes. We also find that the peak of the malaria transmission occurs when the monthly mean temperature is in the range of ~28–29 °C, and monthly rainfall accumulation in the range of ~200–360 mm.

Malaria Risk Map Using Spatial Multi-Criteria Decision Analysis along Yunnan Border During the Pre-elimination Period

“… 80 , 81 A study in India using both a model and observations also reported that malaria vector abundance is higher during the summer monsoon season, and the intensity of malaria transmission is higher with the mosquito populations and the number of infective bites, particularly in forest or mountainous ecotypes. 82 Contrarily, other studies reported forest clearance which provides abundant new habitat for vector species is a classic cause of the emergence of malaria problems, 83 and vectors are found within 5 km of deforested areas. 26 A study in the Amazon area also suggested that deforestation and other human environmental alterations had changed in the presence of both mosquito larvae and adults; although forest clearance and pollution may reduce the availability of larval sites for one species, it may conversely increase habitats preferred by another species.…”

A Threshold Criteria for Seasonal Amplification and Outbreaks of Mosquito-Borne Disease (MBD) Cases in Kerala using Climate Parameters

“…India shows different state/regional gradation in terms of number of malaria and dengue cases(Das et al 2012; Gupta et al 2012; Singh Parihar et al 2019). Prevention of such localized VBD outbreaks like malaria and dengue and timely intervention to reduce the disease burden is important from community health practice perspective.…”

“…Epidemiological modelling and simulation studies often relate the vector growth and proliferation dynamics to the ambient weather and climatic factors like temperature, humidity, rainfall etc. (Loevinsohn 1994; Craig et al 1999; Paaijmans et al 2009; Laneri et al 2010; Hii et al 2012; Lunde et al 2013; Singh Parihar et al 2019; Patil and Pandya 2021; Colón-González et al 2021). The studies showed that temporal evolution of these climate factors provides necessary “forcing” for temporal evolution dynamics.…”

“…what climate forcing leads to larger malaria/dengue cases. Parametric models describing vector dynamics deals with large number of parameters(Taghikhani and Gumel 2018; Singh Parihar et al 2019; Lee et al 2021) and can be often sensitive to these parameters. The non-parametric relationship is simplistic and data driven and would be useful as it is found that there is linear as well as noise and non-linearity mixed relationship between malaria and several climate variables which imparts non-stationarity in the data and hence can be less reliable.…”

Development of a probabilistic early health warning system based on meteorological parameters

“…A study 10 has proposed a set of transmission windows for Indian region, in terms of different temperature ranges for a particular range of relative humidity and found that, the malaria-prone regions may shift from central Indian regions to the south-western and northern States by the 2050s and it is likely to persist over north-eastern parts of the country. Using a dynamical model for malaria transmission, a recent study has identified that a particular range of rainfall (~ 200–360 mm/month) and temperature (monthly mean of ~ 28–29 are favourable for malaria outbreaks over the State of Odisha, India mainly during monsoon months 11 . Another study 12 has evaluated the impacts of climatic parameters (maximum and minimum temperatures and rainfall) on malaria epidemics and the effectiveness of malaria control during the epidemics in India.…”