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Not AvailableImportance: Corona virus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the pandemic claiming millions of lives since the first outbreak was reported in Wuhan, China during December 2019. It is thus important to make cross-country comparison of the relevant rates and understand the socio-demographic risk factors. Methods: This is a record based retrospective cohort study. Table 1 was extracted from https://www.worldometers.info/coronavirus/ and from the Corona virus resource center (Table 2, Figures 1-3), Johns Hopkins University. Data for Table 1 includes all countries which reported >1000 cases and Table 2 includes 20 countries reporting the largest number of deaths. The estimation of CFR, RR and PR of the infection, and disease pattern across geographical clusters in the world is presented. Results: From Table 1, we could infer that as on 4th May 2020, COVID-19 has rapidly spread world-wide with total infections of 3,566,423 and mortality of 248,291. The maximum morbidity is in USA with 1,188,122 cases and 68,598 deaths (CFR 5.77%, RR 15% and PR 16.51%), while Spain is at the second position with 247,122 cases and 25,264 deaths (CFR 13.71%, RR 38.75%, PR 9.78%). Table 2 depicts the scenario as on 8th October 2020, where-in the highest number of confirmed cases occurred in US followed by India and Brazil (cases per million population: 23,080, 5007 & 23,872 respectively). For deaths per million population: US recorded 647, while India and Brazil recorded 77 and 708 respectively. Conclusion: Studying the distribution of relevant rates across different geographical clusters plays a major role for measuring the disease burden, which in-turn enables implementation of appropriate public healthcare measures.Not Availabl

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Not AvailableAntimicrobial resistance (AMR) due to the emergence and spread of extended-spectrum beta-lactamase (ESBL) producing bacteria are becoming a serious global public health concern. This article aims to assess the overall prevalence of ESBLs among animals in India, with year-wise, zone-wise and species-wise stratification. Systematic search from PubMed, Google Scholar and J-Gate Plus was carried out and 24 eligible articles from 2013–2019 in India were retrieved. The R Open source Scripting software was used to perform statistical analysis. The overall prevalence of ESBLs among animals in India was 9%. The pooled prevalence of ESBLs in animals were 26, 11, 6 and 8% for north, east, south and central zones, respectively. The reported prevalence of ESBLs in animals were 12, 5, 8, 8, 12, 13 and 33% were reported for the years 2013, 2014, 2015, 2016, 2017, 2018, 2019 respectively. The species-wise stratified results showed a predominance of ESBL producing Klebsiella pneumoniae strains (11%) when compared to Escherichia coli and Pseudomonas spp. which were 7% and 5%, respectively. The prevalence data generated could be utilized in infection control and in antibiotic use management decisions for developing appropriate intervention strategies.Not Availabl

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Not AvailableAntimicrobial resistance (AMR) due to the emergence and spread of extended-spectrum beta-lactamase (ESBL) producing bacteria are becoming a serious global public health concern. This article aims to assess the overall prevalence of ESBLs among animals in India, with year-wise, zone-wise and species-wise stratification. Systematic search from PubMed, Google Scholar and J-Gate Plus was carried out and 24 eligible articles from 2013–2019 in India were retrieved. The R Open source Scripting software was used to perform statistical analysis. The overall prevalence of ESBLs among animals in India was 9%. The pooled prevalence of ESBLs in animals were 26, 11, 6 and 8% for north, east, south and central zones, respectively. The reported prevalence of ESBLs in animals were 12, 5, 8, 8, 12, 13 and 33% were reported for the years 2013, 2014, 2015, 2016, 2017, 2018, 2019 respectively. The species-wise stratified results showed a predominance of ESBL producing Klebsiella pneumoniae strains (11%) when compared to Escherichia coli and Pseudomonas spp. which were 7% and 5%, respectively. The prevalence data generated could be utilized in infection control and in antibiotic use management decisions for developing appropriate intervention strategies.Not Availabl

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Not AvailableThe Indian poultry industry is one of the fast-growing sectors of which duck farming plays an important role. Duck population in India is 33.51 million that is concentrated towards north-east and southern parts of the country who rears mainly for eggs and meat. Duck diseases are of great concern as they badly affect the financial status of the small, landless farmers. Databases such as Google Scholar, PubMed, J gate were used to search articles between 2000 and 2019 that showed the prevalence of viral, bacterial, and parasitic duck diseases. R open source software was used to derive forest plots by statistical analysis. Pooled prevalence estimates of duck diseases worldwide was found to be 20% (95%-CI:15–26). Also, continent-wise analysis of all duck diseases has revealed highest prevalence in North America, followed by Asia, Africa, Europe,Oceania and South America. This prevalence of data would be helpful to the policymakers to develop appropriate intervention strategies to prevent and control diseases in their respective locationsNot Availabl