Several studies have been conducted on human exposure to ultrafine particulate matter (UFPM), Black carbon (BC), and polystyrene nanoplastics (PS-NPs). However, it remains unclear whether different chemical types of environmental nanoparticles induce a similar mitochondrial stress response or a unique particle-specific response. In the present study, we examined the molecular mechanisms underlying nanoparticle-induced mitochondrial stress response and immunotoxicity using human peripheral blood mononuclear cells exposed to UFPM, BC, and PS-NPs under similar experimental conditions. Oxidative stress, mitochondrial adaptation, respiratory chain integrity, mitochondrial integrated stress response, inflammatory signaling, and systems-level interactions between molecules were analyzed through the evaluation of the expression of NRF2, HIF-1α, PGC-1α, TFAM, OMA1, DELE1, mitochondrial ND1, Complex I-V, NF-κB, TNF-α, and NLRP3 and the use of principal component analysis, hierarchical clustering, and correlation networks. All three nanoparticles caused oxidative stress and mitochondrial dysfunction with different kinetics and mechanisms. UFPM mostly induced an acute antioxidant response and mitochondrial adaptation; BC led to chronic mitochondrial dysfunction, chronic activation of the OMA1-DELE1-mediated mitochondrial ISR pathway, and inflammation; while PS-NPs induced low but chronic mitochondrial adaptation along with mitochondrial biogenesis and stress responses. Our systems-level analysis showed that oxidative stress, mitochondrial adaptation, mitochondrial ISR, and inflammation represent a highly connected molecular network regardless of the physicochemical nature of the nanoparticles, with the OMA1-DELE1 axis being a key regulatory node connecting mitochondrial stress response and inflammation. Overall, we have found that mitochondrial stress response is a common mechanism underlying the toxicity of chemically different nanoparticles and have also revealed particle-specific stress-response dynamics responsible for the degree and persistence of cellular damage. The current work presents novel insights into the molecular mechanisms of nanoparticle-induced immunotoxicity and suggests OMA1, DELE1, NRF2, PGC-1α, TFAM, ND1, and Complex I-V as potential biomarkers.

Aedes aegypti (Linnaeus, 1762), a major arboviral vector of global importance, demonstrates high adaptability across diverse environments. In India, Ae. aegypti is widespread across the country, thriving in highly diverse environmental conditions. Given its genetic, behavioral, and physiological variability, this study investigated whether environmental factors also influence phenotypic traits such as wing morphology across the diverse climatic conditions of India. Right wings from 256 female Ae. aegypti specimens across 12 populations in five major climatic regions of India, viz., Arid, Semi-Arid, Tropical Wet and Dry, Mountain, and Humid Subtropical, were analyzed for morphometric variation. Significant differences in wing centroid size (CS) and shape were observed among both the populations and climatic regions. Arid region (3.95 ± 0.56) and Nagpur population (4.49 ± 0.31) exhibited the largest wings, while Mountain region (Srinagar population) showed the smallest (1.93 ± 0.11). Canonical Variate Analysis (CVA) revealed significant wing shape differences among both populations and regions, with the Semi-Arid region and Kota population showing distinct divergence. Cross-validated reclassification demonstrated high accuracy, with 79

Understanding the genetic structure and diversity of Aedes aegypti (Linnaeus, 1762) populations is critical for predicting transmission dynamics and implementing effective vector control strategies. This study assessed the genetic diversity, population structure, and influence of geography and climate on Ae. aegypti populations across India. Of 308 genotyped individuals, 257 high-quality genotypes from 13 collection sites across 6 climatic regions were retained for analysis using 10 microsatellite loci. High genetic diversity was observed across all populations, consistent with substantial effective population sizes and ongoing gene flow. Moderate but biologically significant genetic differentiation was detected (global FST = 0.077), with the majority of genetic variation occurring within populations (AMOVA: 91.62%). Clustering analyses revealed weak to moderate population structuring, identifying approximately 3 genetic clusters with substantial admixture. Population assignment tests further supported extensive connectivity, with 42% of individuals assigned to nonnative populations. Bottleneck analyses found no recent demographic contractions, and all populations exhibited allele frequency distributions consistent with mutation-drift equilibrium. The Mantel test revealed no significant isolation by distance, suggesting that geographic separation alone does not drive genetic differentiation. Redundancy analysis further indicated that climatic and geographic variables did not significantly explain overall genetic variation, although partial analyses suggested a modest independent contribution of spatial structure. Overall, the genetic structure of Ae. aegypti in India may be influenced by human-mediated dispersal and local ecological processes rather than by broad geographic or climatic constraints. These findings highlight the importance of considering population connectivity in region-specific vector surveillance and control programs.

Aedes aegypti, the primary vector of dengue, chikungunya, Zika, and yellow fever, shows high ecological plasticity across India, yet its population genetic structure remains poorly understood. This study investigates the genetic diversity and spatial differentiation of Ae. aegypti from 13 geographically and climatically diverse regions of India using partial mitochondrial cytochrome oxidase I (COI) gene sequences. A total of 126 individuals revealed 21 haplotypes, with moderate haplotype diversity (mean Hd = 0.55) and low nucleotide diversity (mean π = 0.00663), suggesting recent common ancestry and limited sequence divergence. A dominant haplotype (Hap_2), shared across all populations in a star-like haplotype network, indicates a widespread ancestral lineage with signs of recent expansion. However, the presence of region-specific haplotypes indicates localized differentiation. Genetic differentiation was significant in certain population pairs, particularly involving Itanagar, Kota, and Thiruvananthapuram, with FST values as high as 0.5262. Principal Coordinates Analysis (PCoA) and SAMOVA supported moderate structuring, while AMOVA showed no significant differentiation based on climatic zones. Redundancy analysis and Mantel tests highlighted that geographic distance explained more genetic variation than climate, although only one spatial variable (geo2) emerged as statistically significant. These findings highlight the dominant role of spatial factors, likely reflecting dispersal barriers or limited gene flow, in shaping population structure. Understanding this heterogeneity is vital, as genetic differentiation may influence vector competence, adaptation potential, and the emergence of insecticide resistance. This study provides baseline genetic insights essential for region-specific vector surveillance and control strategies across India's diverse eco-climatic landscape.

BackgroundAedes aegypti is the primary arboviral vector globally, and its affinity to feed on human hosts is a key determinant of transmission intensity. Despite the epidemiological importance of anthropophily, the genomic architecture underlying the molecular basis of host-feeding behavior remains understudied.MethodsHere, we present an integrated genome-wide association study (GWAS) and structural variant analysis of host-feeding behavior in 21 field-collected Ae. aegypti females phenotyped as human-blood-fed (HF; n = 11) or non-human-blood-fed (NHF; n = 10). Whole-genome sequencing yielded 661,519 high-quality SNPs distributed across all three chromosomes. Principal component analysis on a linkage disequilibrium-pruned dataset revealed modest population structure (PC1 = 11.69%, PC2 = 10.98%).ResultsGWAS using a general linear model with five PC covariates (λ = 1.05) identified 11 suggestive SNPs in genes including an actin binding protein on chromosome 2 and G-protein coupled receptor 39 on chromosome 3. Chromosomal inversion analysis using Delly identified an HF-specific inversion on chromosome 2 harboring 13 genes across three functionally coherent chemosensory categories: the sensory developmental regulator tap, odorant receptors (Or6, Or31, Or33) and an odorant-binding protein (Gp68), and eight gustatory receptor genes (Gr15–Gr19a, Gr35, Gr36, Gr66).ConclusionThe concentration of co-adapted chemosensory genes within a single non-recombining chromosomal unit is consistent with a possible supergene model of anthropophily, paralleling inversion-mediated behavioral divergence in Anopheles gambiae. These exploratory findings provide a preliminary genomic framework for host-seeking behavior in Ae. aegypti and identify probable candidate loci warranting functional validation before application to vector surveillance.

IntroductionRecent studies have detected nanoplastics (NPs) in human tissues and biological fluids, raising concerns regarding their potential effects on cellular homeostasis. Nevertheless, their effects on mitochondrial regulation and mitoepigenetic processes remain poorly understood. This work aimed to study the polymer-specific effects of NPs, including polystyrene (PS), polypropylene (PP), and polyvinyl chloride (PVC), on mitochondrial function, mitochondrial homeostasis, oxidative stress generation, inflammatory response, and mitoepigenetics.MethodsCell uptake of NPs was examined using flow cytometry and fluorescence microscopy. Analysis of mitochondrial membrane potential (Δψm), oxidative phosphorylation (OXPHOS), Mitochondrial reactive oxygen species (mtROS) generation, respiratory chain complexes, DNA damage repair enzymes, DNA methylation-related markers, inflammatory cytokines, and mitochondrial gene expression was performed at different time points after NP treatment. Moreover, docking analysis was performed to investigate the potential interactions between oxidized nanoplastic-derived oligomers and mitochondrial Complex I. The relationship between respiratory chain function and mtDNA expression was analyzed using regression.ResultsThe observed effects of the tested NPs included specific effects of each polymer type, such as increased mtROS production, reduced Δψm, induction of oxidative DNA damage, dysregulation of mitochondrial dynamics, and activation of inflammatory pathways. The stress response was characterized by downregulation of DNA methyltransferases, changes in methylation marker levels, and alterations in mitochondrial gene expression. Functional analysis identified Complex I as particularly vulnerable to the effects of NP treatment. The correlation study demonstrated the coordinated regulation of stress-response mediators in mitochondria, namely, DRP1, OMA1, DELE1, and MT-ND6. Meanwhile, the regression analysis showed a correlation between MT-ND6 expression and Complex I activity.DiscussionCollectively, these findings suggest that environmentally relevant NPs elicit polymer-dependent mitochondrial stress responses, mitoepigenetic remodeling, and inflammatory activation.

The geographic expansion of Aedes aegypti, an arboviral disease vector of global importance, is driven by urbanization, global travel, and climate change. Temperature significantly impacts the life cycle, distribution, and vectorial capacity of disease vectors. This study investigates the effects of temperature on the developmental biology, survival, reproductive traits, and wing morphometry of Ae. aegypti populations from central India (Bhopal, Madhya Pradesh). Larvae collected from the field were reared at controlled temperatures, on the basis of the historical and projected temperature changes, ranging from 10 ℃ to 40 ℃. Aedes stage-specific developmental times and survivorship rates were determined and compared. The right wings of male and female mosquitoes reared at 20 °C, 26 °C, and 32 °C were used for morphometric analysis on the basis of the digitized coordinates of 18 landmarks on the wing veins. Higher temperature (32 °C) significantly accelerated life cycle completion, whereas 37 ℃ led to larval survival but high pupal mortality. In contrast, moderate temperatures (26 °C) optimized survival, reproductive output, and extended oviposition periods. Life table analysis revealed that elevated temperatures, particularly at 32 ℃, increased the intrinsic rate of population growth (rm) and shortened generation times, indicating faster population turnover under warmer conditions. However, this rapid life cycle presents trade-offs, including lower survival and reproductive success, which could significantly impact vector population dynamics in the context of climate-driven temperature fluctuations. Wing morphometric analysis further revealed that mosquitoes reared at 32 °C and 26 °C had significantly smaller wings compared with those reared at 20 °C. Although smaller wings may limit dispersal capacity, previous studies suggest a possible link with increased host-seeking and enhanced vectorial potential at 32 °C. This study highlights that Ae. aegypti populations from Central India exhibit thermal tolerance and developmental plasticity under elevated temperatures, suggesting their potential to thrive in warm climates. Rapid development and smaller wing size at higher temperatures may influence survival, fecundity, and biting behavior. Such traits can enhance disease transmission risks by supporting more frequent human–vector contact and sustaining mosquito populations in broader geographic areas.

Antibiotic resistance poses a critical global health threat, demanding robust surveillance systems to monitor its prevalence, patterns, and trends. The One Health approach has emerged as a comprehensive framework, emphasizing the interconnectedness of human health, animal health, and the environment in addressing this complex issue. This article explores the potential of One Health-based antibiotic resistance surveillance, integrating big data analytics and interdisciplinary collaboration. Challenges and opportunities in harmonizing surveillance efforts across sectors are discussed, underscoring the importance of data sharing and standardization. Advanced technologies like genomics and metagenomics are examined for understanding the genetic basis of antibiotic resistance and tracking its spread. The article also highlights the potential of real-time monitoring and early warning systems to inform evidence-based policies and antimicrobial stewardship programs. By analyzing the state-of-the-art in antibiotic resistance surveillance, this article sheds light on the transformative potential of One Health approaches, leveraging big data and interdisciplinary collaboration to combat antibiotic resistance effectively. The urgency of adopting a united global effort to safeguard the efficacy of antibiotics for future generations is emphasized.

OBJECTIVES:The study aimed to isolate and identify bacteriophages specific to drug-resistant Acinetobacter baumannii from hospital sewage, while also characterizing the phenotypic and genotypic resistance mechanisms of the bacterial isolates, including efflux pump activity and biofilm formation. Notably, this research addresses a critical gap in the available literature, as no prior studies have reported the isolation and characterization of bacteriophages targeting A. baumannii in Bhopal or the broader Madhya Pradesh region (India). By exploring the therapeutic potential of bacteriophages in this underrepresented geographic area, this study contributes to the global understanding of phage therapy against multidrug-resistant (MDR) infections. METHODS:A. baumannii strains were isolated from hospital sewage and confirmed via PCR targeting the blaOXA-51-like gene. Antibiotic susceptibility testing was performed to determine resistance profiles. Efflux pump activity, biofilm formation, and molecular resistance determinants were assessed. Lytic bacteriophages targeting MDR A. baumannii were isolated from sewage and characterized via TEM, RAPD-PCR, host range and bacterial reduction assay, one-step growth and stability analyses. RESULTS:Four identified A. baumannii isolates exhibited MDR and extensively drug-resistant (XDR) profiles, with the coexistence of blaOXA-23 and blaNDM-1 genes. Efflux pump activity was detected in two isolates, and biofilm formation varied depending on sugar sources. Five bacteriophages were isolated, showing lytic activity against two MDR A. baumannii isolates. Phage Abp1 demonstrated strong bacterial reduction with a 30-min latent period and burst size of 68 PFU/cell with the highest titre at 37 °C and near neutral pH. CONCLUSION:This study provides the first report of bacteriophage isolation and characterization against MDR A. baumannii in Bhopal, Madhya Pradesh (India), filling a significant research gap in this region. The findings highlight the potential of bacteriophages as therapeutic agents against MDR A. baumannii infections, particularly in hospital settings. By linking bacterial resistance traits with phage efficacy, this study reinforces the role of phage therapy as a promising alternative to conventional antibiotics.

Recent advances in microbiome research have illuminated the complex bidirectional interactions between gut health and reproductive well-being. Understanding the gut microbiome's influence on the reproductive system and vice versa reveals how both of them can affect hormone production, immune function, and ultimately overall reproductive health. Dysbiosis, an imbalance in the gut microbial community, has been linked with a range of reproductive issues, including decreased sperm count and motility, erectile dysfunction, polycystic ovary syndrome (PCOS), endometriosis, infertility, and adverse pregnancy outcomes. This review critically evaluates emerging therapeutic interventions aimed at restoring microbial balance and enhancing reproductive health, such as use of prebiotics, probiotics, bacteriophage therapy, and fecal microbiota transplantation (FMT). By exploring the intricate interplay between gut microbiota and reproductive health, this review also emphasizes the need for integrated approaches in research and clinical practice to develop effective microbiome-based therapies for better reproductive health outcomes.

Predicting dengue distribution based on environmental factors is crucial for effective vector control and management as environmental factors like temperature, demographics, and artificial changes such as roads and buildings significantly influence dengue distribution. The use of new, emerging machine-learning techniques can aid in accurately predicting these cases and developing early warning systems. In this study, we divided our study area, Bhopal city, into 643 polygons of one square kilometre area and collected data on environmental and other factors. Dengue cases from 2012 to 2022 were mapped into these units and divided them into five categories. To find the best predictive model, we evaluated popular machine learning algorithms such as support vector machine (SVM), logistic regression, neural networks, random forest, k-Nearest Neighbors (kNN), and tree using parameters like area under the receiver operating characteristic (ROC) curve (AUC), classification accuracy (CA), F1 score, precision, and recall. The neural network performed the best, with an AUC of 0.921, CA of 0.755, F1 score of 0.740, precision of 0.732, and recall value of 0.755 and was thus selected for future predictions. Among the predictors, building area, population and road density had the highest influence, followed by minimum, maximum, and average temperatures in decreasing order of importance. The machine learning approach neural network effectively predicted the historical dengue distribution considering both landscape and climatic variables for an urban settings like Bhopal. This approach holds potential for application in other cities as well, highlighting the increasing importance of machine learning and predictive modelling in public health.

Background India, with the largest population and second-highest type 2 diabetes mellitus (T2DM) prevalence, presents a unique genetic landscape. This study explores the genetic profiling of T2DM, aiming to bridge gaps in existing research and provide insights for further explorations. Methods We conducted a systematic review and meta-analysis of literature published up to September 2024 using databases like PubMed, Web of Science, Scopus, and Google Scholar to identify SNPs associated with T2DM in case–control studies within the Indian population. Data extraction followed a rigorously designed checklist independently verified by two reviewers. The quality of the studies assessed by utilizing Newcastle Ottawa scale, and heterogeneity through Cochran's Q, τ2, H2 and I2 statistics. Fixed effect and random effect model was employed for meta-analysis based on heterogeneity, and publication bias was assessed by funnel plot analysis, Egger's and Begg's statistical test. In SNPs with adequate studies meta-regression was used to assess source of heterogeneity. Statistical analyses were performed using Stata 18.0 software. Findings Our search identified 1309 articles, with 67 included in the systematic review and 35 in the meta-analysis. These 67 case–control studies, involving 33,407 cases and 30,762 controls, analyzed 167 SNPs across 61 genes. Of these, 89 SNPs mapped to 46 genes showed significant associations with T2DM risk (P < 0.05), including 67 linked to increased risk and 16 with protective effects. Geographical analysis highlighted inter- and intra-regional variations. Meta-analysis of 25 SNPs revealed 12 SNPs with high T2DM risk compatibility. TCF7L2 gene exhibited a strong compatibility with an overall OR of 1.44 (95% CI 1.36–1.52) and S-value 112.41, while TCF7L2 variants rs7903146 and rs12255372, with OR 1.56 (95% CI 1.43–1.66) and S-value 89.036, OR of 1.36 (95% CI 1.17–1.35) with an S-value of 15.45 respectively. Interpretation Our study highlights the importance of considering the diverse ethnic groups of India for development of targeted and effective T2DM management strategies. Funding Department of Biotechnology (DBT) and Indian Council of Medical Research (ICMR), Government of India.

In recent years, the health impacts of phthalates and bisphenol-A (BPA) have garnered significant research attention due to their widespread use in consumer products and identification as endocrine disrupting chemicals (EDCs). Human exposure occurs through various pathways, including dietary intake, inhalation of dust, and dermal contact. This study initially aimed to analyze serum samples from 200 participants in Jabalpur city (Central India); however, samples from 173 individuals were ultimately analyzed to assess the occurrence, concentration patterns, and gender-related differences of six phthalates and BPA. Serum samples were collected, processed, and analyzed for EDC content using gas chromatography coupled with mass spectrometry. The findings highlighted differences in detection frequencies among genders and residential areas, shaped by environmental exposure variability, lifestyle variations, and gender-specific metabolic disparities. All the targeted analytes were detected with diethyl phthalate (DEP) having the highest mean concentration of 13.74 ± 6.2 ng/ml, followed by di(2-ethylhexyl) phthalate (DEHP) with mean value of 13.69 ± 99.82 ng/ml in human serum. Studies have linked DEP exposure endocrine disruption and reproductive abnormalities. Subsequent research endeavors should prioritize elucidating EDC sources, pathways, and health impacts, facilitating evidence-based policies to mitigate risks and ensure a healthier future.

Type-2 diabetes mellitus (T2DM) is a global epidemic with significant societal costs. The gut microbiota, including its metabolites, plays a pivotal role in maintaining health, while gut dysbiosis is implicated in several metabolic disorders, including T2DM. Although data exists on the relationship between the gut bacteriome and metabolic disorders, further attention is needed for the mycobiome and virome. Recent advancements have begun to shed light on these connections, offering potential avenues for preventive measures. However, more comprehensive investigations are required to untangle the interrelations between different microbial kingdoms and their role in T2DM development or mitigation. This review presents a simplified overview of the alterations in the gut bacteriome in T2DM and delves into the current understanding of the mycobiome and virome’s role in T2DM, along with their interactions with the cohabiting bacteriome. Subsequently, it explores into the age-related dynamics of the gut microbiome and the changes observed in the microbiome composition with the onset of T2DM. Further, we explore the basic workflow utilized in gut microbiome studies. Lastly, we discuss potential therapeutic interventions in gut microbiome research, which could contribute to the amelioration of the condition, serve as preventive measures, or pave the way towards personalized medicine.

Airborne nanoplastics constitute an emerging class of environmental contaminants, but their mitoepigenetic effects on human immune cells have not been systematically investigated. Ex vivo human lymphocytes were used to investigate integrated mitochondrial, epigenetic, and inflammatory responses induced by polystyrene (PS), polypropylene (PP), and polyvinyl chloride (PVC) nanoplastics. Fluorescence microscopy at multiple exposure time points and flow cytometry confirmed efficient cellular internalization and progressive intracellular accumulation of nanoplastics. Exposure elicited coordinated transcriptional remodeling of genes regulating mitochondrial dynamics (DRP1, MFN1), mitochondrial DNA encoded oxidative phosphorylation components (MT-ATP6, MT-COX1, MT-ND6), DNA repair (OGG1, APE1), DNA methylation machinery (DNMT1, DNMT3a, DNMT3b), and mitochondrial-associated miRNAs (miR-21, miR-34a, miR-155). Functional analyses revealed polymer and time-dependent disruption of mitochondrial membrane potential and respiratory chain activities, with Complex I identified as the primary site of vulnerability. Correlation analysis showed strong positive associations among DRP1, OMA1, DELE1, and ND6 (r > 0.9, R^2 > 0.8, p < 0.001), reflecting coordinated mitochondrial stress and epigenetic signaling, while negative correlations between DRP1 and MFN1 (r = -0.54, R^2 = 0.29, p < 0.01) and between APE and ND6 (r ≈ -0.42, R^2 ≈ 0.18, p < 0.05) highlight antagonistic regulation and impaired mitochondrial network stability linked to Complex I dysfunction. In silico docking of oxidized nanoplastic oligomers identified high-affinity interactions at the Complex I Fe-S cluster and cofactor-binding sites, suggesting direct interference with electron transfer. A random forest-based model accurately predicted MT-ND6 expression from Complex I activity (R^2 > 0.85), establishing a data-driven Complex I-ND6 axis. Collectively, these findings demonstrate that airborne nanoplastics induce integrated mitoepigenetic and immunometabolic dysregulation, underpinned by coordinated and antagonistic regulatory interactions in lymphocytes. ### Competing Interest Statement The authors have declared no competing interest. ICMR National Institute for Research in Environmental Health, https://ror.org/008bp5f48

Antibiotics, often viewed as a solution, are now recognized as a double-edged sword due to their widespread and improper use. As the global demand for poultry products rises, antibiotics have become a seemingly indispensable tool to meet this need. However, while this practice addresses production demands, it leaves significant health concerns. The emergence of antibiotic-resistant bacteria (ARBs) and antibiotic-resistant genes (ARGs) marks the beginning of a series of unpredictable and potentially undefendable diseases. The topic of zoonosis has gained considerable attention recently, highlighting the intricate connections between humans, animals, and the environment. This review explores the specific impacts of antibiotics—particularly ARGs and ARBs—within the poultry industry, examining the driving factors behind their rise. By delving into the One Health concept, which underscores the interconnectedness of these three domains, the review also discusses innovative strategies to minimize antibiotic use in poultry farming which are vital for preventing and controlling zoonotic diseases, ensuring a healthier environment, and ultimately achieving optimal public health across all tiers of One Health.

The global consumption of bottled water has surged, particularly where safe drinking water is scarce Plastic water bottles may leachharmful Endocrine Disrupting Chemicals (EDCs), including bisphenol-A (BPA) and phthalate esters (PAEs), into the water. This study analyzes BPA and six PAEs in bottled water from various brands in Central India, utilizing gas chromatography-mass spectrometry (GC-MS). A total of 39 samples from 13 brands were analyzed. The results show detectable levels of BPA (35.397 mu g/L to 273.513 mu g/L) and PAEs (ND to 1147.340 mu g/L), with significant concentrations of di-n-butyl phthalate (DBP), bis(2-ethylhexyl) phthalate (DEHP), and BPA, posing potential health risks. A risk assessment based on hazard quotients (HQ) indicated that DEHP and BPA exceeded safe exposure thresholds for non-carcinogenic and anti-androgenic risks. Additionally, DEHP exhibited a carcinogenic risk. These findings emphasize the need for stricter regulations and continuous monitoring to mitigate the health risks associated with EDC exposure from bottled water.

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.

Recent pandemics, including the COVID-19 outbreak, have brought up growing concerns about transmission of zoonotic diseases from animals to humans. This highlights the requirement for a novel approach to discern and address the escalating health threats. The One Health paradigm has been developed as a responsive strategy to confront forthcoming outbreaks through early warning, highlighting the interconnectedness of humans, animals, and their environment. The system employs several innovative methods such as the use of advanced technology, global collaboration, and data-driven decision-making to come up with an extraordinary solution for improving worldwide disease responses. This Review deliberates environmental, animal, and human factors that influence disease risk, analyzes the challenges and advantages inherent in using the One Health surveillance system, and demonstrates how these can be empowered by Big Data and Artificial Intelligence. The Holistic One Health Surveillance Framework presented herein holds the potential to revolutionize our capacity to monitor, understand, and mitigate the impact of infectious diseases on global populations.

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.