In a stark reminder of the 1918 Spanish flu that made the world poorer by 50 million humans, COViD 19 has set many industries on a path financial losses, while people struggle to come to terms with the disruption to their lives.
Urbanization influenced malaria prevalence has escalated over the past two decades in India. According to the UN Department of economics and social affairs, 55% of the world’s population lives in urban areas, which is expected to increase up to 68% by the year 2050 (UN Department of Economics and Social Affairs, 2018).
Forecasting public health expenditure by the Government of India is an important aspect to assess the government’s effectiveness towards disease control and policy implications. Assessing the trend in the public healthcare expenditure by the central government, predicted that the public health expenditure will get doubled in the next five years.
Political epidemiology towards infectious disease management primarily identifies needed factors for the evaluation of the efficacy of policies. These factors comprise of cases of incidence, mortality, and demographic values.
Plasmodium genus causes an estimated 438,000 global deaths annually. In India, mainly two species of Plasmodium is prevalent, Plasmodium falciparum and Plasmodium vivax (Siwal, et al., 2018). P. vivax accounts for 53% of the total malaria cases in India.
Associated malarial risk factors are largely favoured by the climatic and economic conditions. It largely occurs in the regions having high rates of precipitation, humidity, and rainfall making it optimum for the malaria vector to breed and flourish.
Meta-analysis study was conducted by using Comprehensive Meta-Analysis (CMA) to assess the government policy effectiveness under the 5-year plan scheme in accordance with the malaria incidence and deaths over the time span of last five year plans.
This article presents state-wise malaria incidence data to test the patterns of prevalence of malaria in India between 2011 and 2015. Geospatial malarial modelling helps in comparing the intervention efficacy with respect to different states in India and the aspect that contribute to its inefficacy.