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Background: Antimicrobial resistance (AMR) is a growing concern globally, but the impact is very deleterious in the context of Bangladesh. Recent review article on the AMR issue demonstrates the scenario in human medicine; unfortunately, no attempt was taken to address this as One Health issue. The antimicrobial resistance bacteria or genes are circulating in the fragile ecosystems and disseminate into human food chain through direct or indirect ways. In this systematic review we are exploring the mechanism or the process of development of resistance pathogen into human food chain via the domestic animal, wildlife and environmental sources in the context of One Health and future recommendation to mitigate this issue in Bangladesh. Results: Tetracycline resistance genes were presenting in almost all sample sources in higher concentrations against enteric pathogen Escherichia coli. The second most significant antibiotics are amino-penicillin that showed resistant pattern across different source of samples. It is a matter of concerns that cephalosporin tends to acquire resistance in wildlife species that might be an indication of this antibiotic resistance gene or the pathogen been circulating in our surrounding environment though the mechanism is still unclear. Conclusions: Steps to control antibiotic release and environmental disposal from all uses should be immediate and obligatory. There is a need for detailed system biology analysis of resistance development in-situ.

South Asian (SA) countries have been fighting with the pandemic novel coronavirus disease 2019 (COVID-19) since January 2020. Earlier, the country-specific descriptive study has been done. Nevertheless, as transboundary infection, the border sharing, shared cultural and behaviour practice, effects on the temporal and spatial distribution of COVID-19 in SA is still unveiled. Therefore, this study has been revealed the spatial hotspot along with descriptive output on different parameters of COVID-19 infection. We extracted data from the WHO and the worldometer database from the onset of the outbreak up to 15 May 2020. Europe has the highest case fatality rate (CFR; 9.22%), whereas Oceania has the highest (91.15%) recovery rate from COVID-19. Among SA countries, India has the highest number of cases (85,790), followed by Pakistan (38,799) and Bangladesh (20,065). However, the number of tests conducted was minimum in this region in comparison with other areas. The highest CFR was recorded in India (3.21%) among SA countries, whereas Nepal and Bhutan had no death record due to COVID-19 so far. The recovery rate varies from 4.75% in the Maldives to 51.02% in Sri Lanka. In Bangladesh, community transmission has been recorded, and the highest number of cases were detected in Dhaka, followed by Narayanganj and Chattogram. Dhaka and its surrounding districts, Faridpur and Madaripur district of Bangladesh, is in the hotspot on the spatiotemporal tendency. But no cold spot was pointed out in Bangladesh. Three hotspots and three cold spots at different confidence levels were detected in India. Findings from this study suggested the “test, trace, and isolation” approach for earlier detection of infection to prevent further community transmission of COVID-19.

The coronavirus disease 2019 (COVID-19) is an emerging and rapidly evolving profound pandemic, which causes severe acute respiratory syndrome and results in significant case fatality around the world including Bangladesh. We conducted this study to assess how COVID-19 cases clustered across districts in Bangladesh and whether the pattern and duration of clusters changed following the country's containment strategy using Geographic information system (GIS) software. We calculated the epidemiological measures including incidence, case fatality rate (CFR) and spatiotemporal pattern of COVID-19. We used inverse distance weighting (IDW), Geographically weighted regression (GWR), Moran's I and Getis-Ord Gi* statistics for prediction, spatial autocorrelation and hotspot identification. We used retrospective space-time scan statistic to analyse clusters of COVID-19 cases. COVID-19 has a CFR of 1.4%. Over 50% of cases were reported among young adults (21-40 years age). The incidence varies from 0.03 -0.95 at the end of March to 15.59-308.62 per 100,000, at the end of July. Global Moran's Index indicates a robust spatial autocorrelation of COVID-19 cases. Local Moran's I analysis stated a distinct High-High (HH) clustering of COVID-19 cases among Dhaka, Gazipur and Narayanganj districts.Twelve statistically significant high rated clusters were identified by space-time scan statistics using a discrete Poisson model. IDW predicted the cases at the undetermined area, and GWR showed a strong relationship between population density and case frequency, which was further established with Moran's I (0.734; p ≤ 0.01). Dhaka and its surrounding six districts were identified as the significant hotspot whereas Chattogram was an extended infected area, indicating the gradual spread of the virus to peripheral districts. This study provides novel insights into the geostatistical analysis of COVID-19 clusters and hotspots that might assist the policy planner to predict the spatiotemporal transmission dynamics and formulate imperative control strategies of SARS-CoV-2 in Bangladesh. The geospatial modeling tools can be used to prevent and control future epidemics and pandemics.

The exact origin of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and source of introduction into humans has not been established yet, though it might be originated from animals. Therefore, we conducted a study to understand the putative reservoirs, transmission dynamics, and susceptibility patterns of SARS-CoV-2 in animals. Rhinolophus bats are presumed to be natural progenitors of SARS-CoV-2related viruses. Initially, pangolin was thought to be the source of spillover to humans, but they might be infected by human or other animal species. So, the virus spillover pathways to humans remain unknown. Human-to-animal transmission has been testified in pet, farmed, zoo and free-ranging wild animals. Infected animals can transmit the virus to other animals in natural settings like mink-to-mink and mink-to-cat transmission. Animal-to-human transmission is not a persistent pathway, while minkto-human transmission continues to be illuminated. Multiple companions and captive wild animals were infected by an emerging alpha variant of concern (B.1.1.7 lineage) whereas Asiatic lions were infected by delta variant, (B.1.617.2). To date, multiple animal species -cat, ferrets, non-human primates, hamsters and bats -showed high susceptibility to SARS-CoV-2 in the experimental condition, while swine, poultry, cattle showed no susceptibility. The founding of SARS-CoV-2 in wild animal reservoirs can confront the control of the virus in humans and might carry a risk to the welfare and conservation of wildlife as well. We suggest vaccinating pets and captive animals to stop spillovers and spillback events. We recommend sustainable One Health surveillance at the animal-human-environmental interface to detect and prevent future epidemics and pandemics by Disease X.