Malaria surveillance is weak in high malaria burden countries. Surveillance is considered as one of the core interventions for malaria elimination. Impressive reductions in malaria-associated morbidity and mortality have been achieved across the globe, but sustained efforts need to be bolstered up to achieve malaria elimination in endemic countries like India.
An early and accurate diagnosis followed by prompt treatment is pre-requisite for the management of any disease. Malaria diagnosis is routinely performed by microscopy and rapid diagnostic tests (RDTs) in the field settings; however, their performance may vary across regions, age and asymptomatic status. Owing to this, we assessed the diagnostic performance of conventional and advanced molecular tools for malaria detection in low and high malaria-endemic settings. We performed mass blood surveys in low and high endemic regions of two North-Eastern districts from the states of Assam and Meghalaya.
Efforts have been made to quantify the spatio-temporal malaria transmission intensity over India using the dynamical malaria model, namely, Vector-borne Disease Community Model of International Centre for Theoretical Physics Trieste (VECTRI). The likely effect of climate change in the variability of malaria transmission intensity over different parts of India is also investigated.
Malaria control system (MCS), an Information technology (IT)-driven surveillance and monitoring intervention is being adopted for elimination of malaria in Mangaluru city, Karnataka, India since October 2015. This has facilitated ‘smart surveillance’ followed by required field response within a timeline. The system facilitated data collection of individual case, data driven mapping and strategies for malaria elimination programme. This paper aims to present the analysis of post-digitization data of 5 years, discuss the current operational functionalities of MCS and its impact on the malaria incidence.
Aminopeptidase N1 (APN) is one of the important enzymes involved in blood digestion and is up-regulated along with several other enzymes in response to bloodmeal ingestion. APN is a zinc metalloprotease that cleaves one amino acid residue at a time from the amino terminus of the protein. The APN1 gene of the Indian malaria vector Anopheles culicifacies Giles was cloned and characterized. The An. culicifacies APN1 (AcAPN1) gene has an Open Reading Frame of 3084 basepairs which encodes a putative protein of 1027 amino acids.
Precise identification of Plasmodium species is critical in malaria control and elimination. Despite several shortcomings, microscopy and rapid diagnostic test (RDT) continue to be the leading diagnostic methods. Polymerase chain reaction (PCR) is the most sensitive method but its dependency on advanced laboratory and skilled workers limits its use.
Malaria Elimination Demonstration Project (MEDP) was started as a Public-Private-Partnership between the Indian Council of Medical Research through National Institute of Research in Tribal Health, Govt. of Madhya Pradesh and Foundation of Disease Elimination and Control of India, which is a Corporate Social Responsibility (CSR) initiative of the Sun Pharmaceutical Industries Limited. The project’s goal was to demonstrate that malaria can be eliminated from a high malaria endemic district along with prevention of re-establishment of malaria and to develop a model for malaria elimination using the lessons learned and knowledge acquired from the demonstration project.
Malaria elimination requires targeting asymptomatic and low-density Plasmodium infections that largely remain undetected. Therefore we conducted a cross-sectional study to estimate the burden of asymptomatic and low-density Plasmodium infection using conventional and molecular diagnostics.
Despite declining incidence over the past decade, malaria remains an important health burden in India. This study aimed to assess the village-level temporal patterns of Plasmodium infection in two districts of the north-eastern state of Meghalaya and evaluate risk factors that might explain these patterns.
The state of Punjab in India qualifies for malaria elimination because the number of cases reported through routine surveillance is in decline. However, surveillance system prevalence mainly provides malaria trends. Therefore, a prospective epidemiological study was designed to estimate the malaria burden in the state.