Addressing low-density malaria infections in India and other endemic part of the world-the opportune time?

Shifting from high- to low-malaria transmission accompanies a higher proportion of asymptomatic low-density malaria infections (LDMI). Currently, several endemic countries, such as India, are experiencing this shift as it is striving to eliminate malaria. LDMI is a complex concept for which there are several important questions yet unanswered on its natural history, infectiousness, epidemiology, and pathological and clinical impact. India is on the right path to eliminating malaria, but it is facing the LDMI problem. A brief discussion on the concept and definitions of LDMI is beforehand presented. Also, an exhaustive review and critical analysis of the existing literature on LDMI in malaria-endemic areas, including India, are included in this review. Finally, we opine that addressing LDMI in India is ethically and pragmatically achievable, and a pool of sine qua non conditions is required to efficiently and sustainably eliminate malaria.

Nationwide spatiotemporal drug resistance genetic profiling from over three decades in Indian Plasmodium falciparum and Plasmodium vivax isolates.

BACKGROUND: Drug resistance is a serious impediment to efficient control and elimination of malaria in endemic areas. METHODS: This study aimed at analysing the genetic profile of molecular drug resistance in Plasmodium falciparum and Plasmodium vivax parasites from India over a ~ 30-year period (1993-2019). Blood samples of P. falciparum and/or P. vivax-infected patients were collected from 14 regions across India. Plasmodial genome was extracted and used for PCR amplification and sequencing of drug resistance genes in P. falciparum (crt, dhps, dhfr, mdr1, k13) and P. vivax (crt-o, dhps, dhfr, mdr1, k12) field isolates. RESULTS: The double mutant pfcrt SVMNT was highly predominant across the country over three decades, with restricted presence of triple mutant CVIET from Maharashtra in 2012. High rates of pfdhfr-pfdhps quadruple mutants were observed with marginal presence of "fully resistant" quintuple mutant ACIRNI-ISGEAA. Also, resistant pfdhfr and pfdhps haplotype has significantly increased in Delhi between 1994 and 2010. For pfmdr1, only 86Y and 184F mutations were present while no pfk13 mutations associated with artemisinin resistance were observed. Regarding P. vivax isolates, the pvcrt-o K10 "AAG" insertion was absent in all samples collected from Delhi in 2017. Pvdhps double mutant SGNAV was found only in Goa samples of year 2008 for the first time. The pvmdr1 908L, 958M and 1076L mutations were highly prevalent in Delhi and Haryana between 2015 and 2019 at complete fixation. One nonsynonymous novel pvk12 polymorphism was identified (K264R) in Goa. CONCLUSIONS: These findings support continuous surveillance and characterization of P. falciparum and P. vivax populations as proxy for effectiveness of anti-malarial drugs in India, especially for independent emergence of artemisinin drug resistance as recently seen in Africa.

A Regional Pooling Intervention in a High-Throughput COVID-19 Diagnostic Laboratory to Enhance Throughput, Save Resources and Time Over a Period of 6 Months.

An effective and rapid diagnosis has great importance in tackling the ongoing COVID-19 pandemic through isolation of the infected individuals to curb the transmission and initiation of specialized treatment for the disease. It has been proven that enhanced testing capacities contribute to efficiently curbing SARS-CoV-2 transmission during the initial phases of the outbreaks. RT-qPCR is considered a gold standard for the diagnosis of COVID-19. However, in resource-limited countries expenses for molecular diagnosis limits the diagnostic capacities. Here, we present interventions of two pooling strategies as 5 sample pooling (P-5) and 10 sample pooling (P-10) in a high-throughput COVID-19 diagnostic laboratory to enhance throughput and save resources and time over a period of 6 months. The diagnostic capacity was scaled-up 2.15-folds in P-5 and 1.8-fold in P-10, reagents (toward RNA extraction and RT-qPCR) were preserved at 75.24% in P-5 and 86.21% in P-10, and time saved was 6,290.93 h in P-5 and 3147.3 h in P-10.