Socializing One Health: an innovative strategy to investigate social and behavioral risks of emerging viral threats

In an effort to strengthen global capacity to prevent, detect, and control infectious diseases in animals and people, the United States Agency for International Development’s (USAID) Emerging Pandemic Threats (EPT) PREDICT project funded development of regional, national, and local One Health capacities for early disease detection, rapid response, disease control, and risk reduction. From the outset, the EPT approach was inclusive of social science research methods designed to understand the contexts and behaviors of communities living and working at human-animal-environment interfaces considered high-risk for virus emergence. Using qualitative and quantitative approaches, PREDICT behavioral research aimed to identify and assess a range of socio-cultural behaviors that could be influential in zoonotic disease emergence, amplification, and transmission. This broad approach to behavioral risk characterization enabled us to identify and characterize human activities that could be linked to the transmission dynamics of new and emerging viruses. This paper provides a discussion of implementation of a social science approach within a zoonotic surveillance framework. We conducted in-depth ethnographic interviews and focus groups to better understand the individual- and community-level knowledge, attitudes, and practices that potentially put participants at risk for zoonotic disease transmission from the animals they live and work with, across 6 interface domains. When we asked highly-exposed individuals (ie. bushmeat hunters, wildlife or guano farmers) about the risk they perceived in their occupational activities, most did not perceive it to be risky, whether because it was normalized by years (or generations) of doing such an activity, or due to lack of information about potential risks. Integrating the social sciences allows investigations of the specific human activities that are hypothesized to drive disease emergence, amplification, and transmission, in order to better substantiate behavioral disease drivers, along with the social dimensions of infection and transmission dynamics. Understanding these dynamics is critical to achieving health security--the protection from threats to health-- which requires investments in both collective and individual health security. Involving behavioral sciences into zoonotic disease surveillance allowed us to push toward fuller community integration and engagement and toward dialogue and implementation of recommendations for disease prevention and improved health security

Transmission Dynamics and Genomic Epidemiology of Emerging Variants of SARS-CoV-2 in Bangladesh

With the progression of the global SARS-CoV-2 pandemic, the new variants have become more infectious and continue spreading at a higher rate than pre-existing ones. Thus, we conducted a study to explore the epidemiology of emerging variants of SARS-CoV-2 that circulated in Bangladesh from December 2020 to September 2021, representing the 2nd and 3rd waves. We collected new cases and deaths per million daily data with the reproduction rate. We retrieved 928 SARS-CoV-2 sequences from GISAID and performed phylogenetic tree construction and mutation analysis. Case counts were lower initially at the end of 2020, during January–February and April–May 2021, whereas the death toll reached the highest value of 1.587 per million on the first week of August and then started to decline. All the variants (α, β, δ, η) were prevalent in the capital city, Dhaka, with dispersion to large cities, such as Sylhet and Chattogram. The B.1.1.25 lineage was prevalent during December 2020, but the B.1.617.2/δ variant was later followed by the B.1.351/β variant. The phylogeny revealed that the various strains found in Bangladesh could be from numerous countries. The intra-cluster and inter-cluster communication began in Bangladesh soon after the virus arrived. The prominent amino acid substitution was D614G from December 2020 to July 2021 (93.5 to 100%). From February–April, one of the VOC’s important mutations, N501Y substitution, was also estimated at 51.8%, 76.1%, and 65.1% for the α, β and γ variants, respectively. The γ variant’s unique mutation K417T was detected only at 1.8% in February. Another frequent mutation was P681R, a salient feature of the δ variant, detected in June (88.2%) and July (100%). Furthermore, only one γ variant was detected during the entire second and third wave, whereas no η variant was observed in this period. This rapid growth in the number of variants identified across Bangladesh shows virus adaptation and a lack of strict quarantine, prompting periodic genomic surveillance to foresee the spread of new variants, if any, and to take preventive measures as soon as possible

Serological evidence of West Nile Virus in wild birds in Bangladesh

West Nile Virus (WNV) is a vector-borne zoonotic disease maintained in a sylvatic cycle involving mosquito vectors and birds. To detect WNV and other flavivirus infections in wild resident and migratory birds, we tested 184 samples from 19 identified species within nine families collected during 2012–2016 from four districts in Bangladesh. We tested serum samples for the immunoglobulin G (IgG) antibody against WNV using competitive Enzyme-Linked Immunosorbent Assay (c-ELISA), whereas tracheal and cloacal swabs were subjected to consensus Polymerase Chain Reaction (c-PCR) for the detection of the flavivirus RNA. Overall, we detected 11.9% (n = 22; 95% CI: 0.07–0.16) samples were seropositive, including 15.9% in the migratory wild birds and 10.7% in the resident wild birds. The migratory wild Tufted duck showed 28.5% seropositivity, whereas the resident wild house crows showed 12.5% seropositivity. None of the swab samples was positive for flavivirus RNA infection (0%, n = 184; 95% CI: 0–0.019). These study findings recommend continued surveillance for early detection and to better understand the epidemiology of WNV and other flavivirus circulation in both birds and mosquitoes in Bangladesh

Transmission Pathways and Genomic Epidemiology of Emerging Variants of SARS-CoV-2 in the Environment

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can spread to the environment through several routes and persist for a more extended period. Therefore, we reviewed pertinent literature to understand the transmission dynamics of SARS-CoV-2 and genomic epidemiology of emerging variants of concern (VOCs) in the environment, their inactivation strategies, and the impact of COVID-19 on the ecosystem. The fallouts of the reviewed studies indicate that SARS-CoV-2 transmits through air and fomite, contaminated surfaces, biomedical wastes, and stool, which contaminates the environment through wastewater. As a result, multiple VOCs of SARS-CoV-2 were circulating in the environment. Genomic epidemiology revealed that the most prevalent VOC was Delta (B.1.617.2; 44.24%), followed by Omicron (B.1.1.529; 43.33%), in the environment. Phylogenetic analysis showed that environmental strains are clustered with a likeness of the human strains of the same or nearby countries, emphasizing the significance of continued environmental surveillance to track the emergence of the new variant. Thus, we should reduce viral dispersion in the environment through rapid and appropriate disinfection strategies. Moreover, the increased production and use of macro and microfiber plastic products should be brought under strict legislation with integrated waste management to control the unrelenting propagation of viral RNA. Finally, a comprehensive understanding of the environmental transmission pathways of SARS-CoV-2 is crucial for forecasting outbreak severity in the community, allowing us to prepare with the correct tools to control any impending pandemic. We recommend wastewater-based SARS-CoV-2 surveillance and air particulates to track the emerging VOCs of SARS-CoV-2 spread in the environment

Molecular Epidemiology of SARS-CoV-2 in Diverse Environmental Samples Globally

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has swamped the global environment greatly in the current pandemic. Wastewater-based epidemiology (WBE) effectively forecasts the surge of COVID-19 cases in humans in a particular region. To understand the genomic characteristics/footprints and diversity of SARS-CoV-2 in the environment, we analyzed 807 SARS-CoV-2 sequences from 20 countries deposited in GISAID till 22 May 2021. The highest number of sequences (n = 638) were reported in Austria, followed by the Netherlands, China, and Bangladesh. Wastewater samples were highest (40.0%) to successfully yield the virus genome followed by a 24 h composite wastewater sample (32.6%) and sewage (18.5%). Phylogenetic analysis revealed that SARS-CoV-2 environmental strains are a close congener with the strains mostly circulating in the human population from the same region. Clade GRY (32.7%), G (29.2%), GR (25.3%), O (7.2%), GH (3.4%), GV (1.4%), S (0.5%), and L (0.4%) were found in environmental samples. Various lineages were identified in environmental samples; nevertheless, the highest percentages (49.4%) of the alpha variant (B.1.1.7) were detected in Austria, Liechtenstein, Slovenia, Czech Republic, Switzerland, Germany, and Italy. Other prevalent lineages were B.1 (18.2%), B.1.1 (9.2%), and B.1.160 (3.9%). Furthermore, a significant number of amino acid substitutions were found in environmental strains where the D614G was found in 83.8% of the sequences. However, the key mutations—N501Y (44.6%), S982A (44.4%), A570D (43.3%), T716I (40.4%), and P681H (40.1%) were also recorded in spike protein. The identification of the environmental belvedere of SARS-CoV-2 and its genetic signature is crucial to detect outbreaks, forecast pandemic harshness, and prepare with the appropriate tools to control any impending pandemic. We recommend genomic environmental surveillance to trace the emerging variants and diversity of SARS-CoV-2 viruses circulating in the community. Additionally, proper disposal and treatment of wastewater, sewage, and medical wastes are important to prevent environmental contamination

Erratum to: Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition) (Autophagy, 12, 1, 1-222, 10.1080/15548627.2015.1100356

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