Spatiotemporal Epidemiology of Malaria in India from 2007 to 2022.

India is a major contributor to the global burden of malaria, especially Plasmodium vivax infection. Understanding the spatiotemporal trends of malaria across India over the last two decades may assist in targeted intervention. The population-normalized spatiotemporal trends of malaria epidemiology in India from 2007 to 2022 were analyzed using a geographic information system with the publicly available "malaria situation" report of the National Vector Borne Disease Control Program (NVBDCP). The NVBDCP data showed malaria cases to have steeply declined from 1.17 million in 2015 to 0.18 million cases in 2022; this is 10.1 and 18.7 fold lower than the WHO's estimate of 11.93 million and 3.38 million cases in 2015 and 2022, respectively. From 2007 to 2022, Mizoram, Meghalaya, Tripura, Odisha, Chhattisgarh, and Jharkhand consistently reported high caseloads of Plasmodium falciparum. In the same period, the P. vivax caseload was high in Arunachal Pradesh, Mizoram, Nagaland, Jharkhand, Odisha, Chhattisgarh, Goa, Daman and Diu, Dadra and Nagar Haveli, and Andaman and Nicobar Islands. The distribution of forest cover, annual rainfall, and proportion of the Scheduled Tribe population (the most underprivileged in Indian society) spatially correlated with malaria cases and deaths. Mizoram is the only state where cases were higher in 2022 than in 2007. Overall, India has made tremendous progress in controlling malaria and malaria-related deaths in the last decade. The decline could be attributed to the effective vector and parasite control strategies implemented across the country.

Spatial epidemiology of acute respiratory infections in children under 5 years and associated risk factors in India: District-level analysis of health, household, and environmental datasets.

Background: In India, acute respiratory infections (ARIs) are a leading cause of mortality in children under 5 years. Mapping the hotspots of ARIs and the associated risk factors can help understand their association at the district level across India. Methods: Data on ARIs in children under 5 years and household variables (unclean fuel, improved sanitation, mean maternal BMI, mean household size, mean number of children, median months of breastfeeding the children, percentage of poor households, diarrhea in children, low birth weight, tobacco use, and immunization status of children) were obtained from the National Family Health Survey-4. Surface and ground-monitored PM2.5 and PM10 datasets were collected from the Global Estimates and National Ambient Air Quality Monitoring Programme. Population density and illiteracy data were extracted from the Census of India. The geographic information system was used for mapping, and ARI hotspots were identified using the Getis-Ord Gi* spatial statistic. The quasi-Poisson regression model was used to estimate the association between ARI and household, children, maternal, environmental, and demographic factors. Results: Acute respiratory infections hotspots were predominantly seen in the north Indian states/UTs of Uttar Pradesh, Bihar, Delhi, Haryana, Punjab, and Chandigarh, and also in the border districts of Uttarakhand, Himachal Pradesh, and Jammu and Kashmir. There is a substantial overlap among PM2.5, PM10, population density, tobacco smoking, and unclean fuel use with hotspots of ARI. The quasi-Poisson regression analysis showed that PM2.5, illiteracy levels, diarrhea in children, and maternal body mass index were associated with ARI. Conclusion: To decrease ARI in children, urgent interventions are required to reduce the levels of PM2.5 and PM10 (major environmental pollutants) in the hotspot districts. Furthermore, improving sanitation, literacy levels, using clean cooking fuel, and curbing indoor smoking may minimize the risk of ARI in children.

Social and housing indicators of dengue and chikungunya in Indian adults aged 45 and above: Analysis of a nationally representative survey (2017-18).

BACKGROUND: Dengue and chikungunya (CHIKV) are the two major vector-borne diseases of serious public health concern in India. Studies on socioeconomic and housing determinants of dengue and CHIKV at a pan-India level are lacking. Here, we took advantage of the recently carried out Longitudinal Ageing Study in India (LASI) carried out across all the states and Union Territories of India to study the social indicators of dengue and CHIKV in India. METHODS: LASI-1 (2017-2018) data on the self-reported period prevalence of dengue and CHIKV from 70,932 respondents aged ≥45 years were used for this analysis. The state-wise distribution of dengue and CHIKV was mapped. Prevalence was estimated for each study variable, and the difference was compared using the χ2 test. The adjusted odds ratios (AOR) of the socioeconomic and housing variables for dengue and CHIKV were estimated using the multiple logistic regression model. RESULTS: Urban residence is the major socio-economic indicator of dengue and CHIKV (dengue AOR: 1.57, 95% CI: 1.18-2.11; CHIKV AOR: 1.84, 95% CI: 1.36-2.49). The other notable indicator is wealth; rich respondents have higher odds of dengue and CHIKV. Adults older than 54 years and those with high school education and above are associated with a lower likelihood of dengue and CHIKV. In addition, CHIKV is associated with scheduled and forward castes, households with improper toilet facilities, open defecation, and kutcha house type. CONCLUSIONS: Despite the limitation that the data is only from adults ≥ 45, this analysis provides important insights into the socioeconomic and housing variables associated with higher odds of dengue and CHIKV in India. Understanding these determinants may assist in the national planning of prevention and control strategies for dengue and CHIKV.

Epidemiology, Hot Spots, and Sociodemographic Risk Factors of Alcohol Consumption in Indian Men and Women: Analysis of National Family Health Survey-4 (2015-16), a Nationally Representative Cross-Sectional Study.

Objectives: To map the alcohol hot spots and understand the Sociodemographic Indices (SDI) affecting alcohol consumption in Indian men and women. Methods: Data from National Family Health Survey-4 carried out from 2015 to 2016 with a sample size of 103,411 men and 699,686 women were used for Geographic Information System mapping, and hot spot identification by spatial statistics (Getis-Ord Gi*). Bivariate analyses and multiple logistic regressions were used to analyze SDI. Results: India has three major alcohol hot spots: (1) North-East (NE) states, (2) Eastern Peninsular states formed by Chhattisgarh, Odisha, Jharkhand, and Telangana, and (3) Southern states of Tamil Nadu and Kerala. Hot spot analysis strongly correlated with region-wise analysis of SDI. Respondents who consumed tobacco have higher odds (men adjusted odds ratio [aOR]: 5.42; women aOR: 4.30) of consuming alcohol. Except for religion and social category, other socioeconomic factors have a low to moderate effect on alcohol consumption. Conclusions: Hot spots and high-risk districts of alcohol consumption identified in this study can guide public health policies for targeted intervention. Alcohol use is at the discretion of individual states and union territories, and stringent anti-alcohol policies strictly enforced across India are the keys to control alcohol use.

Socio-economic and household determinants of malaria in adults aged 45 and above: analysis of longitudinal ageing survey in India, 2017-2018.

BACKGROUND: Even though malaria cases have drastically come down in the last decade, malaria remains a serious public health concern in many parts of India. National Framework for Malaria Elimination in India (2016-2030) has been launched with the goal to eliminate malaria by 2030. Understanding the socio-economic and household determinants of malaria at the national level will greatly aid India's malaria elimination efforts. METHODS: The data from Longitudinal Ageing Survey of India (LASI) Wave 1 (2017-2018) survey comprising 70,671 respondents ≥ 45 years across all the States and Union Territories were used for the analysis. Simple and multiple logistic regressions were used to obtain the unadjusted and adjusted odds ratio respectively of the socio-economic and household variables. RESULTS: The major socio-economic variables that increase the likelihood of malaria are caste ('scheduled tribes'), low education levels and rural residence. The scheduled tribes have 1.8 times higher odds of malaria than the scheduled castes (AOR: 1.8; 95% CI: 1.5-2.1). Respondents with high school education (6-12 grade) (AOR: 0.7; 95% CI: 0.6-0.8) and college education (AOR: 0.5; 95% CI: 0.4-0.6) had a very low risk of malaria than those with no school years. Rural residence and occupation (agriculture and allied jobs) also increases the odds of malaria. The major housing determinants are household size (≥ 6), housing type (kutcha), use of unclean fuel, outside water source, improper sanitation (toilet facilities) and damp wall/ceiling. CONCLUSIONS: The study has identified the major socio-economic and housing factors associated with malaria in adults aged 45 and above. In addition to vector and parasite control strategies in the tribal dominated regions of India, improving literacy and housing conditions may help India's malaria elimination efforts.

Functional studies of Plasmodium falciparum's prohibitin1 and prohibitin 2 in yeast.

Prohibitins (PHBs) are evolutionarily conserved mitochondrial integral membrane proteins, shown to regulate mitochondrial structure and function, and can be classified into PHB1 and PHB2. PHB1 and PHB2 have been shown to interact with each other, and form heterodimers in mitochondrial inner membrane. Plasmodium falciparum has orthologues of PHB1 and PHB2 in its genome, and their role is unclear. Here, by homology modelling and yeast two-hybrid analysis, we show that putative Plasmodium PHBs (Pf PHB1 and Pf PHB2) interact with each other, which suggests that they could form supercomplexes of heterodimers in Plasmodium, the functional form required for optimum mitochondrial function.

Seroprevalence and risk factors of brucellosis in livestock in the wildlife and livestock interface area of Similipal Biosphere Reserve, India.

BACKGROUND AND AIM: Brucellosis is an important zoonotic disease that affects fertility in farm animals. The risk factors of brucellosis have not been well studied. This study aimed to understand the seroprevalence and risk factors of brucellosis among livestock in Bangriposi block of Mayurbhanj district in Odisha, a region that borders Similipal wildlife reserve. MATERIALS AND METHODS: Rose Bengal plate test (RBPT) was carried out to estimate the seroprevalence of the livestock in this region. Bivariate analysis was carried out to analyze the association between the variables and brucellosis. Binary logistic regression was performed to assess the risk factors associated with brucellosis in the livestock. RESULTS: Based on RBPT, the seroprevalence of brucellosis among cattle and goats was estimated to be 1.1% and 11.2%, respectively. Binary logistic regression analysis indicates that study area, age, goats, animals with a history of abortion, and rearing practices were the major risk factors in this region. CONCLUSION: This is one of the first studies in India to shed light on risk factors of brucellosis, an important neglected disease that affects the health of animals and humans and nation's economy.

Functional studies of Plasmodium falciparum putative SURF1 in Saccharomyces cerevisiae.

BACKGROUND AND OBJECTIVES: The mitochondrial electron transport chain (mtETC) of Plasmodium falciparum is an important drug target. Identification and functional validation of putative mitochondrial proteins of the mtETC is critical for drug development. Many of the regulatory subunits and assembly factors of cytochrome c oxidase readily identifiable in humans and yeast are missing in P. falciparum. Here, we describe our efforts to identify and validate the function of putative Pfsurf1, a key assembly factor of complex IV of the mtETC. METHODS: Multiple sequence alignment of SURF 1/Shy 1 was carried out in Clustal X 2.1. Phylogenetic tree was constructed using "Draw tree" option in Clustal X, and was analyzed using interactive Tree of Life software. To identify the conserved sequences, domain search was done using Jalview version 2.8.2 (BLOSUM 62 scoring). The haploid Saccharomyces cerevisiae strain (BY4741) containing the null allele shy1 (Orf: YGR112w) (shy1::Kan) was complemented with putative Pfsurf1 to study its ability to rescue the growth defect. RESULTS: Similarity searches of PfSURF1-like protein in the Pfam shows statistically significant E = 4.7e-10 match to SURF1 family. Sequence alignment of PfSURF1 with other SURF1-like proteins reveals the conservation of transmembrane domains, α-helices and ß-pleated sheets. Phylogenetic analysis clusters putative PfSURF1 with apicomplexan SURF1-like proteins. Yeast complementation studies show that Pfsurf1 can partially rescue the yeast shy1 mutant, YGR112w. INTERPRETATION & CONCLUSION: Bioinformatics and complementation studies in yeast show that P. falciparum's SURF1 is the functional ortholog of human SURF1 and yeast Shy1.

Malaria in North-East India: Importance and Implications in the Era of Elimination.

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.