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.

Polymerase Spiral Reaction (PSR) as a point-of-care diagnostic assay: A systematic review.

INTRODUCTION: The current systematic review aimed to collect and analyze the comprehensive evidence regarding Polymerase Spiral Reaction (PSR) and to estimate its diagnostic performance and usefulness as a point-of-care (PoC) assay. METHODS: Literature was retrieved systematically from 2015 to 2023 from PubMed and Scopus. Studies were screened and selected against pre-determined inclusion and exclusion criteria. Quality assessment and risk of bias were critiqued using QUADAS-2. A systematic, qualitative narrative synthesis was employed to synthesize the data. RESULTS: 11 studies were selected for the systematic review, testing diseases in humans utilizing PSR. Only 2 studies clinically validated the test with a sample size > 150. 5 studies were of poor quality; 3 studies were of moderate quality and 3 studies were deemed to be of high quality. 3 studies quantified the diagnostic throughput and reported clinical sensitivity and specificity of PSR approaching to be > 92% and ~ 100%, respectively. CONCLUSION: Polymerase spiral reaction promises to be an optimistic isothermal assay; however, a huge research gap can be attributed to the lack of statistical and clinical evidence to validate the assay. Adequate research, focused on optimization, coupled with statistical and clinical validation, can help in estimating its true diagnostic potential and applicability. REGISTRATION AND PROTOCOL: A detailed protocol of this review is registered and available in Prospero (registration number CRD42023406265).

Spatio-temporal epidemiology and associated indicators of COVID-19 (wave-I and II) in India.

The spatio-temporal distribution of COVID-19 across India's states and union territories is not uniform, and the reasons for the heterogeneous spread are unclear. Identifying the space-time trends and underlying indicators influencing COVID-19 epidemiology at micro-administrative units (districts) will help guide public health strategies. The district-wise daily COVID-19 data of cases and deaths from February 2020 to August 2021 (COVID-19 waves-I and II) for the entire country were downloaded and curated from public databases. The COVID-19 data normalized with the projected population (2020) and used for space-time trend analysis shows the states/districts in southern India are the worst hit. Coastal districts and districts adjoining large urban regions of Mumbai, Chennai, Bengaluru, Goa, and New Delhi experienced > 50,001 cases per million population. Negative binomial regression analysis with 21 independent variables (identified through multicollinearity analysis, with VIF < 10) covering demography, socio-economic status, environment, and health was carried out for wave-I, wave-II, and total (wave-I and wave-II) cases and deaths. It shows wealth index, derived from household amenities datasets, has a high positive risk ratio (RR) with COVID-19 cases (RR: 3.577; 95% CI: 2.062-6.205) and deaths (RR: 2.477; 95% CI: 1.361-4.506) across the districts. Furthermore, socio-economic factors such as literacy rate, health services, other workers' rate, alcohol use in men, tobacco use in women, overweight/obese women, and rainfall have a positive RR and are significantly associated with COVID-19 cases/deaths at the district level. These positively associated variables are highly interconnected in COVID-19 hotspot districts. Among these, the wealth index, literacy rate, and health services, the key indices of socio-economic development within a state, are some of the significant indicators associated with COVID-19 epidemiology in India. The identification of district-level space-time trends and indicators associated with COVID-19 would help policymakers devise strategies and guidelines during public health emergencies.

Prediction, Synthesis and Evaluation of a Synthetic Peptide as an Enzyme-Linked Immunosorbent Assay (ELISA) Candidate for Screening of Bovine Antibodies against Theileria annulata.

Tick-borne diseases (TBDs) of livestock are endemic across various parts of tropical countries. Theileriosis is one such economically important TBD, caused by the Theileriidae family of organisms, which is transmitted by ticks. Theileria annulata, the causative agent of tropical theileriosis, contributes a significant loss to the dairy sector by causing anorexia, high fever, anemia, inflammatory changes in vital organs and icterus, thus, a loss in milk yield. Though vaccines are available, their protective efficacy is not absolute, and treatment is limited to early diagnosis of the causative agent. Routinely, microscopic identification of piroplasms in the erythrocytes (Giemsa-stained) of infected animals or schizonts in lymph node biopsies are practiced for diagnosis. PCR-based techniques (multiplex, uniplex, nested and real-time) have been reported to perform well in diagnosing active infection. Several attempts have been made using serological assays like Dot blot, ELISA and ICT, but the results were of variable sensitivity and specificity. Recombinant proteins like the Theileria annulata merozoite surface antigen (Tams1) and Theileria annulata surface protein (TaSP) have been explored as antigenic candidates for these assays. In the present study, we predicted an immunogenic peptide, i.e., TaSP-34, from the TaSP using various computational tools. The predicted peptide was custom synthesized. The diagnostic potential of the peptide was assessed by indirect plate ELISA to detect the bovine-IgM against Theileria annulata. Alongside, a recombinant truncated TaSP (rTaSP(tr)) was expressed and purified, which was used to compare the performance of the peptide as a diagnostic candidate. The IgM-based peptide ELISA was 100% sensitive and 92.77% specific as compared to PCR (Tams1 targeting), while 98.04% sensitivity and 97.44% specificity were observed in comparison with rTaSP(tr) ELISA. Almost perfect agreement between peptide ELISA and Tams1 PCR was observed with a Cohen's kappa coefficient (κ-value) of 0.901 and agreement of 95.31%. Further, the κ-value between the peptide ELISA and rTaSP(tr) ELISA was found to be 0.95, and the agreement was 97.65%, which shows a good correlation between the two tests. The findings suggest that the TaSP-34 peptide can be an efficient and new-generation diagnostic candidate for the diagnosis of T. annulata. Furthermore, the peptide can be synthesized commercially at a larger scale and can be a cost-effective alternative for the protein-based diagnostic candidates for T. annulata.

Isothermal amplification technology (IAT) for rapid diagnosis of Rickettsioses: scope, overview, existing evidence, and the way forward.

Rickettsioses, a category of zoonosis primarily caused by Rickettsia and Orientia, is a huge cause of public health concern worldwide. Diseases like murine typhus, scrub typhus, Mediterranean spotted fever and rocky mountain spotted fever are major contributors of Rickettsioses globally, with peculiar distributions in south-east Asia, Africa, Arabia and the Americas. With the innovations in molecular diagnostics, Isothermal Amplification Technology is gaining popularity for its fidelity, rapidity and cost-effectiveness. Compared to commercial assays, they are easily adaptable for point-of-care (PoC) settings. Due to nonspecific presentation as an acute undifferentiated febrile illness, diagnosis of Rickettsioses poses a great challenge. Certain isothermal amplification assays have proven to be highly efficient in diagnosing vector borne diseases like dengue, malaria, and chikungunya. The purpose of this review is to provide readers the current advancements, scope, challenges, and future prospects of isothermal amplification technologies in the detection of zoonotic pathogens like Rickettsia and Orientia.

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.

Diagnosis of Human Leptospirosis: Comparison of Microscopic Agglutination Test with Recombinant LigA/B Antigen-Based In-House IgM Dot ELISA Dipstick Test and Latex Agglutination Test Using Bayesian Latent Class Model and MAT as Gold Standard.

Leptospirosis is a spirochaetal infection that possesses a broad host range affecting almost all mammals. In the present study, the microscopic agglutination test (MAT) was compared with recombinant LigA/B antigen-based point-of-care diagnostics such as the in-house IgM dot ELISA dipstick test (IgM- DEDT) and the latex agglutination test (LAT) for the serodiagnosis of human leptospirosis. The comparison of the MAT with these two point-of-care diagnostics was performed using the MAT as the gold standard test and using Bayesian latent class modelling (BLCM), which considers all diagnostic tests as imperfect. The N-terminal conserved region of the LigA/B protein spanning the first to fifth big tandem repeat domains (rLigA/BCon1-5) was employed as a serodiagnostic marker in both of the bedside assays. A total of 340 serum samples collected from humans involved in high risk occupations were screened using the MAT, IgM DEDT and LAT. During the early phase of leptospirosis, BLCM analysis showed that the IgM DEDT and LAT had similar sensitivities (99.6 (96.0-100)) and (99.5 (95.2-100)), respectively, while the single acute phase MAT had the lowest sensitivity (83.3 (72.8-91.3)). Both the IgM DEDT and the LAT may be superior to the single acute phase MAT in terms of sensitivity during the early phase of infection and may be suitable for the early diagnosis of leptospirosis. However, BLCM analysis revealed that the use of both acute and convalescent samples substantially increased the sensitivity of the final MAT (98.2% (93.0-99.8%)) as a test to diagnose human leptospirosis. Both the IgM DEDT and LAT can be employed as bedside spot tests in remote locations where the MAT is not easily accessible.

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.

Immunoinformatic Study of Recombinant LigA/BCon1-5 Antigen and Evaluation of Its Diagnostic Potential in Primary and Secondary Binding Tests for Serodiagnosis of Porcine Leptospirosis.

Leptospirosis is responsible for hampering the productivity of swine husbandry worldwide. The aim of this study was to assess the efficacy of bioinformatics tools in predicting the three-dimensional structure and immunogenicity of recombinant LigBCon1-5 (rLigBCon1-5) antigen. A battery of bioinformatics tools such as I-TASSER, ProSA and SAVES v6.0 were used for the prediction and assessment of the predicted structure of rLigBCon1-5 antigen. Bepipred-2.0, DiscoTope v2.0 and ElliPro servers were used to predict linear and conformational epitopes while T-cell epitopes were predicted using NetMHCpan 4.1 and IEDB recommended 2.22 method for MHC Class I and II peptides respectively. The results obtained using various in silico methods were then compared with wet lab experiments comprising of both primary (IgG Dot ELISA Dipstick test) and secondary-binding assays (Latex Agglutination Test [LAT]) to screen 1153 porcine serum samples. The three-dimensional structure of rLigA/BCon1-5 protein as predicted by I-TASSER was found to be reliable by Ramachandran Plot and ProSA. The ElliPro server suggested 10 and three potential linear and conformational B-cell-epitopes, respectively, on the peptide backbone of the rLigA/BCon1-5 protein. The DiscoTope prediction server suggested 47 amino acid residues to be part of B-cell antigen. Ten of the most efficient peptides for MHC-I and II grooves were predicted by NetMHCpan 4.1 and IEDB recommended 2.22 method, respectively. Of these, three peptides can serve dual functions as it can fit both MHC I and II grooves, thereby eliciting both humoral-and cell-mediated immune responses. The prediction of these computational approaches proved to be reliable since rLigBCon1-5 antigen-based IgG Dot ELISA Dipstick test and LAT gave results in concordance to gold standard test, the Microscopic Agglutination Test (MAT), for serodiagnosis of leptospirosis. Both the IgG Dot ELISA Dipstick test and LAT were serodiagnostic assays ideally suited for peripheral level of animal health care system as "point of care" tests for the detection of porcine leptospirosis.

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.

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.

Biosynthesis, characterization and antimicrobial activity of silver nanoparticles by Streptomyces sp. SS2.

In the present study the microbial biosynthesis of silver nanoparticles (AgNPs) by secondary metabolites of Streptomyces sp. SS2 in an eco-friendly approach has been reported. The Streptomyces sp. SS2 was isolated from the soil sediment of Similipal Biosphere Reserve. The identification of this strain was determined by phenotypical characteristics (morphological and biochemical) and molecular characterization method using 16 s rDNA sequencing. The morphological study was also done by high-resolution scanning electron microscopy. The preliminary characterization of biosynthesized silver nanoparticle was carried out using UV-Vis spectrum analysis, which showed an absorption peak at 420 nm corresponding to plasmon absorption of silver. The average size and charge (zeta potential) of the particles were found to be 67.95 ± 18.52 nm and -17.7 ± 5.30 mV, respectively. The functional groups were identified by FTIR studies and their morphology (round and spherical shape) was determined by scanning electron microscopy. The synthesized AgNPs exhibited excellent antibacterial activity against Escherichia coli (MTCC 1089), Bacillus subtilis (MTCC 7164), Staphylococcus epidermis (MTCC 3615), Vibrio cholerae (MTCC 3904) and Staphylococcus aureus (MTCC 1144). These biotechnological approaches of synthesis of nanoparticles can direct a new path in biomaterial sciences and enrich biomedical applications.