Worldwide and in India, malaria elimination efforts are being ramped up to eradicate the disease by 2030. Malaria elimination efforts in North-East (NE) India will have a great bearing on the overall efforts to eradicate malaria in the rest of India. The first cases of chloroquine and sulfadoxine-pyrimethamine resistance were reported in NE India, and the source of these drug resistant parasites are most likely from South East Asia (SEA). NE India is the only land route through which the parasites from SEA can enter the Indian mainland. India’s malaria drug policy had to be constantly updated due to the emergence of drug resistant parasites in NE India. Malaria is highly endemic in many parts of NE India, and Plasmodium falciparum is responsible for the majority of the cases. Highly efficient primary vectors and emerging secondary vectors complicate malaria elimination efforts in NE India. Many of the high transmission zones in NE India are tribal belts, and are difficult to access. The review details the malaria epidemiology in seven NE Indian states from 2008 to 2018. In addition, the origin and evolution of resistance to major anti-malarials are discussed. Furthermore, the bionomics of primary vectors and emergence of secondary malaria vectors, and possible strategies to prevent and control malaria in NE are outlined.

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In recent decades, dengue has been expanding rapidly in the tropical cities. Even though environmental factors and landscape features profoundly impact dengue vector abundance and disease epidemiology, significant gaps exist in understanding the role of local environmental heterogeneity on dengue epidemiology in India. In this study, we assessed the role of remotely sensed climatic factors (rainfall, temperature and humidity) and landscape variables (land use pattern, vegetation and built up density) on dengue incidence (2012–2019) in Bhopal city, Central India. Dengue hotspots in the city were assessed through geographical information system based spatial statistics. Dengue incidence increased from 0.59 cases in 2012 to 9.11 cases in 2019 per 10,000 inhabitants, and wards located in Southern Bhopal were found to be dengue hotspots. Distributed lag non-linear model combined with quasi Poisson regression was used to assess the exposure-response association, relative risk (RR), and delayed effects of environmental factors on dengue incidence. The analysis revealed a non-linear relationship between meteorological variables and dengue cases. The model shows that the risk of dengue cases increases with increasing mean temperature, rainfall and absolute humidity. The highest RR of dengue cases (~2.0) was observed for absolute humidity ≥60 g/m3 with a 5–15 week lag. Rapid urbanization assessed by an increase in the built-up area (a 9.1% increase in 2020 compared to 2014) could also be a key factor driving dengue incidence in Bhopal city. The study sheds important insight into the synergistic effects of both the landscape and climatic factors on the transmission dynamics of dengue. Furthermore, the study provides key baseline information on the climatic variables that can be used in the micro-level dengue prediction models in Bhopal and other cities with similar climatic conditions.