Geo-environmental factors and the effectiveness of mulberry leaf extract in managing malaria.

Malaria prevalence has become medically important and a socioeconomic impediment for the endemic regions, including Purulia, West Bengal. Geo-environmental variables, humidity, altitude, and land use patterns are responsible for malaria. For surveillance of the endemic nature of Purulia's blocks, statistical and spatiotemporal factors analysis have been done here. Also, a novel approach for the Pf malaria treatment using methanolic leaf extract of Morus alba S1 has significantly reduced the parasite load. The EC50 value (1.852) of the methanolic extract of M. alba S1 with P. falciparum 3D7 strain is close to the EC50 value (0.998) of the standard drug chloroquine with the same chloroquine-sensitive strain. Further studies with an in-silico model have shown successful interaction between DHFR and the phytochemicals. Both 1-octadecyne and oxirane interacted favourably, which was depicted through GC-MS analysis. The predicted binary logistic regression model will help the policy makers for epidemiological surveillance in malaria-prone areas worldwide when substantial climate variables create a circumstance favourable for malaria. From the in vitro and in silico studies, it can be concluded that the methanolic extract of M. alba S1 leaves were proven to have promising antiplasmodial activity. Thus, there is a scope for policy-driven approach for discovering and developing these lead compounds and undermining the rising resistance to the frontline anti-malarial drugs in the world.

Study of epidemiological behaviour of malaria and its control in the Purulia district of West Bengal, India (2016-2020).

Purulia is a malaria-prone district in West Bengal, India, with approximately half of the blocks defined as malaria endemic. We analyzed the malaria case in each block of the Purulia district from January 1, 2016, to December 31, 2020. As per the API, 20 blocks of Purulia were assigned to four different categories (0-3) and mapped using ArcGIS software. An exponential decay model was fitted to forecast the trend of malaria cases for each block of Purulia (2021-2025). There was a sharp decrease in total malaria cases and API from 2016 to 2020 due to the mass distribution of LLINs. The majority of cases (72.63%) were found in ≥ 15-year age group. Males were more prone to malaria (60.09%). Malaria was highly prevalent among Scheduled Tribes (48.44%). Six blocks were reported in Category 3 (high risk) and none in Category 0 (no risk) in 2016, while no blocks were determined to be in Category 3, and three blocks were in Category 0 in 2020. The exponential decay model prediction is oriented towards gaining malaria-free status in thirteen blocks of Purulia by 2025. This study will incite the government to uphold and strengthen the current efforts to meet the malaria elimination goals.