Kamala Jain’s scientific contributions

Malaria remains a significant public health problem in India. Although temperature influences Anopheline mosquito feeding intervals, population density, and longevity, the reproductive potential of the Plasmodium parasite and rainfall influence the availability of larval habitats, and evidence to correlate the impact of climatic factors on the incidence of malaria is sparse. Understanding the influence of climatic factors on malaria transmission will help us predict the future spread and intensification of the disease. The present study aimed to determine the impact of temporal trend of climatic factors such as annual average maximum, minimum, mean temperature, and rainfall on the annual incidence of malaria cases in India for a period of 61 years from 1961 to 2021 and relative humidity for a period of 41 years from 1981 to 2021. Two different analyses were performed. In the first analysis, the annual incidence of malaria and meteorological parameters such as annual maximum, minimum, and mean temperature, annual rainfall, and relative humidity were plotted separately in the graph to see if the temporal trend of climatic factors had any coherence or influence over the annual incidence of malaria cases. In the second analysis, a scatter plot was used to determine the relationship of the incidence of malaria in response to associated climatic factors. The incidence of malaria per million population was also calculated. In the first analysis, the annual malaria cases showed a negative correlation of varying degrees with relative humidity, minimum, maximum, and mean temperature, except rainfall, which showed a positive correlation. In the second analysis, the scatter plot showed that the rainfall had a positive correlation with malaria cases, and the rest of the climatic factors, such as temperature and humidity, had negative correlations of varying degrees. Out of the total 61 years studied, in 29 years, malaria cases increased more than 1000 square root counts when the minimum temperature was at 18–19 °C; counts also increased over a period of 33 years when the maximum temperature was 30–31 °C, over 37 years when the mean temperature was 24–25 °C, over 20 years when the rainfall was in the range of 100–120, and over a period of 29 years when the relative humidity was at 55–65%. While the rainfall showed a strong positive correlation with the annual incidence of malaria cases, the temperature and relative humidity showed negative correlations of various degrees. The increasing temperature may push the boundaries of malaria towards higher altitude and northern sub-tropical areas from the southern peninsular region. Although scanty rainfall reduces the transmission, increases in the same would increase the malaria incidence in India.

Background Malaria remains a significant public health problem in India. Although temperature influences Anopheline mosquito feeding intervals, population density, and longevity, the reproductive potential of the Plasmodium parasite and rainfall influences the availability of larval habitats, evidence to correlate the climatic factors with malaria is limited. Understanding the influence of climatic factors on malaria will help us predict the disease's future spread and intensification. Hence, the temporal trend of climatic factors such as annual average maximum, minimum, mean temperature, and rainfall was compared with the annual incidence of malaria cases in India for the period of 61 years from 1961 to 2021 and relative humidity for the period of 41 years from 1981 to 2021 to find out the relationship of climatic factors on the incidence of malaria cases. Methods Two different analyses were done. In the first analysis, the annual incidence of malaria and the meteorological parameters such as annual maximum, minimum, and mean temperature, annual rainfall, and relative humidity were plotted separately with each of the climatic factors in the graph to see if the temporal trend of climatic factors has any coherence or influence over the annual incidence of malaria cases. A polynomial trendline at order 6 that showed the maximum R² value was drawn for malaria cases and each of the meteorological factors. The Pearson correlation coefficient was calculated for both square roots of malaria cases vs. each of the climatic factors. The P-value, R²-value, and N-value were also determined. In the second analysis, a multiple linear regression model was used to identify the associated climatic factors with malaria cases. The prevalence of malaria per million population was also calculated. Results In the first analysis, the annual malaria cases showed a negative correlation of varying degrees with relative humidity, minimum, maximum, and mean temperature, except for rainfall which showed a positive correlation. In the second analysis, out of the total 61 years studied, in 29 years, malaria cases went more than 1000 square root when the minimum temperature was at 18°-19°C, 33 years when the maximum temperature was 30°-31°, 37 years when the mean temperature was 24°-25°, 20 years when the rainfall was in the range of 100–120 and 29 years when the relative humidity was at 55–65%.