Emerging pandemics: Connections with environment and climate change

Pandemics are often associated with viruses and bacteria occurring in wildlife in natural environments. Thus, diseases of epidemic and pandemic scale are mostly zoonotic, some of which include AIDS, Zika virus, severe acute respiratory syndrome (SARS), and COVID-19. The book seeks to explore the documented history of pandemics and various epidemics that have the potential of turning into pandemics with the warming climate, pollution, and environmental destruction. The book covers some of the most essential elements of the diseases of pandemic nature and their relationship with the environment: Environment as a reservoir of human diseases. Climate change: emerging driver of infectious diseases. Occurrence and environmental dimensions of specific pandemics and epidemics. Pandemics, environment, and globalisation: understanding the interlinkage in the context of COVID-19. Climate change and zoonotic diseases: malaria, plague, dengue, encephalitis. Tuberculosis: an old enemy of mankind and possible next pandemic. Lassa fever in Nigeria: case fatality ratio, social consequences, and prevention. There are cases where scientists fear that many epidemics have the potential of turning into pandemics, if we do not pay attention to them, and measures are not being taken to control these occurrences. This book attempts to provide integrated risk assessment on pandemics like COVID-19. It covers fundamental factors of global disease outbreaks through the complexity and severity of consequences. The information collated in this book will help in the design of mitigation measures, including behavioral changes that could prevent the emergence of such pandemics, thus protecting human life and minimising losses incurred due to diseases of such magnitude. © All rights reserved.

Tracking SARS-CoV-2 variants through pandemic waves using RT-PCR testing in low-resource settings.

COVID-19 resulted in extensive morbidity and mortality worldwide. SARS-CoV-2 evolved rapidly, with increasing transmission due to Variants of Concern (VOC). Identifying VOC became important but genome submissions from low-middle income countries (LMIC) remained low leading to gaps in genomic epidemiology. We demonstrate the use of a specific mutation RT-PCR based approach to identify VOC in SARS-CoV-2 positive samples through the pandemic in Pakistan. We selected 2150 SARS-CoV-2 PCR positive respiratory specimens tested between April 2021 and February 2022, at the Aga Khan University Hospital Clinical Laboratories, Karachi, Pakistan. Commercially available RT-PCR assays were used as required for mutations in Spike protein (N501Y, A570D, E484K, K417N, L452R, P681R and deletion69_70) to identify Alpha, Beta, Gamma, Delta, and Omicron variants respectively. Three pandemic waves associated with Alpha, Delta and Omicron occurred during the study period. Of the samples screened, VOC were identified in 81.7% of cases comprising mainly; Delta (37.2%), Alpha (29.8%) and Omicron (17.1%) variants. During 2021, Alpha variants were predominant in April and May; Beta and Gamma variants emerged in May and peaked in June; the Delta variant peaked in July and remained predominant until November. Omicron (BA.1) emerged in December 2021 and remained predominant until February 2022. The CT values of Alpha, Beta, Gamma and Delta were all significantly higher than that of Omicron variants (p<0.0001). We observed VOC through the pandemic waves using spike mutation specific RT-PCR assays. We show the spike mutation specific RT-PCR assay is a rapid, low-cost and adaptable for the identification of VOC as an adjunct approach to NGS to effectively inform the public health response. Further, by associating the VOC with CT values of its diagnostic PCR we gain information regarding the viral load of samples and therefore the level of transmission and disease severity in the population.

Evaluation of 3-D printed swabs for respiratory sampling and testing for SARS-CoV-2 during the early pandemic period (preprint)

Appropriate collection of respiratory samples is essential for accurate diagnostic testing of respiratory pathogens such as, SARS-CoV-2. Early in the pandemic, there was a shortage of nasopharyngeal (NP) swabs and difficulty in sampling suspected cases. Therefore, we developed a 3D printed nasal swab for anterior nares, paired with in-house viral transport medium (VTM). The utility of this 3D swab kit was investigated in comparison with the standard NP commercial swab and VTM, in 200 individuals between August and September 2021. Subjects were those presenting for diagnostic testing for SARS-CoV-2 using the RT-PCR (cobas Roche assay) assay. NP samples were taken from each subject using the standard NP and 3D swabs followed by RT-PCR on paired specimens. CT values for amplification of gene targets were evaluated to determine assay parameters based on viral load cut offs of [≤] CT 35 or, [≤] CT 37. For high to medium viral loads, 3D swab based PCR testing had a sensitivity of 93%, specificity of 99%, positive predictive value (PPV) of 98.5% and negative predictive value (NPV) of 96.2% respectively. For low viral loads, 3D swab testing had a sensitivity of 88%, specificity of 99%, with a PPV of 98.5% and NPV of 93.2%.%. 3D swab sampling of anterior nares was comparable with NP sampling using standard swabs for SARS-CoV-2 specimens with a medium to high viral load. Therefore, 3D swab based sampling is a reliable and convenient local solution for collecting respiratory samples for SARS-CoV-2 diagnostic testing.

Insights from establishing a high throughput viral diagnostic laboratory for SARS-CoV-2 RT-PCR testing facility: challenges and experiences.

Background: The World Health Organization declared the coronavirus disease 2019 (COVID-19) a global pandemic on 11 March 2020. Identifying the infected people and isolating them was the only measure that was available to control the viral spread, as there were no standardized treatment interventions available. Various public health measures, including vaccination, have been implemented to control the spread of the virus worldwide. India, being a densely populated country, required laboratories in different zones of the country with the capacity to test a large number of samples and report test results at the earliest. The Indian Council of Medical Research (ICMR) took the lead role in developing policies, generating advisories, formulating guidelines, and establishing and approving testing centers for COVID-19 testing. With advisories of ICMR, the National Institute of Cancer Prevention and Research (NICPR) established a high-throughput viral diagnostic laboratory (HTVDL) for RT-PCR-based diagnosis of SARS-CoV-2 in April 2020. HTVDL was established during the first lockdown to serve the nation in developing and adopting rapid testing procedures and to expand the testing capacity using "Real-Time PCR." The HTVDL provided its testing support to the national capital territory of Delhi and western Uttar Pradesh, with a testing capacity of 6000 tests per day. The experience of establishing a high-throughput laboratory with all standard operating procedures against varied challenges in a developing country such as India is explained in the current manuscript which will be useful globally to enhance the knowledge on establishing an HTVDL in pandemic or non-pandemic times.

Assessment of anxiety and fear of getting infected among dentists while working in current corona virus disease outbreak- A study

Background: Health care workers and dentists in particular are categorized as at high risk of catching Covid- 19 infection. The present study assessed anxiety and fear among dentists while working in current corona virus pandemic. Material(s) and Method(s): 150 dentists of both genders were provided with a questionnaire. Each positive response "Yes" was marked as "1" while "No" was marked with "0." The frequency of the positive/negative responses was used to assess the dentists' anxiety. Result(s): Out of 150 subjects, males were 90 and females were 60. 70 were BDS, 80 were MDS, 50 were working in clinic, 60 in hospital and 40 in both, 95 were working in private sector and 55 in government sector. The anxiety of being infected with COVID-19 was seen in 67%, afraid of providing treatment for any patient was seen in 70%, anxious talking to the patients in close proximity in 65%, afraid that you could carry the infection from your practice back to your family in 84%, feel anxious when you hear that one of your coworkers or colleagues has been infected with COVID-19 in 80% and 72% knew the illness problems associated with COVID-19 virus. The difference was significant (P< 0.05). Conclusion(s): Dentists had anxiety and fear while working in Covid- 19 pandemic.Copyright © 2020 Ubiquity Press. All rights reserved.

Transmission of SARS-CoV-2 in the Population Living in High- and Low-Density Gradient Areas in Dhaka, Bangladesh.

Community transmission of SARS-CoV-2 in densely populated countries has been a topic of concern from the beginning of the pandemic. Evidence of community transmission of SARS-CoV-2 according to population density gradient and socio-economic status (SES) is limited. In June-September 2020, we conducted a descriptive longitudinal study to determine the community transmission of SARS-CoV-2 in high- and low-density areas in Dhaka city. The Secondary Attack Rate (SAR) was 10% in high-density areas compared to 20% in low-density areas. People with high SES had a significantly higher level of SARS-CoV-2-specific Immunoglobulin G (IgG) antibodies on study days 1 (p = 0.01) and 28 (p = 0.03) compared to those with low SES in high-density areas. In contrast, the levels of seropositivity of SARS-CoV-2-specific Immunoglobulin M (IgM) were comparable (p > 0.05) in people with high and low SES on both study days 1 and 28 in both high- and low-density areas. Due to the similar household size, no differences in the seropositivity rates depending on the population gradient were observed. However, people with high SES showed higher seroconversion rates compared to people with low SES. As no difference was observed based on population density, the SES might play a role in SARS-CoV-2 transmission, an issue that calls for further in-depth studies to better understand the community transmission of SARS-CoV-2.

Leading Predictors of COVID-19-Related Poor Mental Health in Adult Asian Indians: An Application of Extreme Gradient Boosting and Shapley Additive Explanations.

During the COVID-19 pandemic, an increase in poor mental health among Asian Indians was observed in the United States. However, the leading predictors of poor mental health during the COVID-19 pandemic in Asian Indians remained unknown. A cross-sectional online survey was administered to self-identified Asian Indians aged 18 and older (N = 289). Survey collected information on demographic and socio-economic characteristics and the COVID-19 burden. Two novel machine learning techniques-eXtreme Gradient Boosting and Shapley Additive exPlanations (SHAP) were used to identify the leading predictors and explain their associations with poor mental health. A majority of the study participants were female (65.1%), below 50 years of age (73.3%), and had income ≥ $75,000 (81.0%). The six leading predictors of poor mental health among Asian Indians were sleep disturbance, age, general health, income, wearing a mask, and self-reported discrimination. SHAP plots indicated that higher age, wearing a mask, and maintaining social distancing all the time were negatively associated with poor mental health while having sleep disturbance and imputed income levels were positively associated with poor mental health. The model performance metrics indicated high accuracy (0.77), precision (0.78), F1 score (0.77), recall (0.77), and AUROC (0.87). Nearly one in two adults reported poor mental health, and one in five reported sleep disturbance. Findings from our study suggest a paradoxical relationship between income and poor mental health; further studies are needed to confirm our study findings. Sleep disturbance and perceived discrimination can be targeted through tailored intervention to reduce the risk of poor mental health in Asian Indians.

COVID-19 diagnostic testing underestimated cases amongst females in Pakistan (preprint)

Objectives Understanding the impact of COVID-19 largely depended on information from PCR based diagnostic testing of SARS-CoV-2. It was recognized early in the pandemic that testing rates varied greatly between high and low income countries. Whilst total numbers of tests conducted are noted, little attention has been made to differences that may be due to gender and we examined this in the context of Pakistan. Methods We conducted a retrospective cross-sectional analysis of respiratory specimens received for SARS-CoV-2 by PCR at Aga Khan University Hospital, Karachi, Pakistan between February 2020 and February 2022. Data was analysed in six monthly intervals; P-I, February to July 2020; P-II, August 2020 to January 2021; P-III, February to July 2021 and August 2021 until February 2022. Results A total of 470,047 PCR tests were conducted. The proportion of tests conducted for females was, 35% in P-I; 40% in P-II; 44% in P-III and 46% in P-III. 21% of specimens were positive for SARS-CoV-2, only 9% of these specimens were from females. The greatest numbers of tests were conducted in males aged 31 to 45 years followed by those aged 16-30 years. The fewest tests were conducted in children aged under 15 years. The highest percentage of PCR positive tests was found in those ages 60 years and above. Compared for gender SARS-CoV-2 positivity rates were comparable across the study period. Conclusions COVID-19 data from Pakistan indicates that there are larger numbers of males as compared with females who were affected by this disease. Our results show that this may be due to a gender bias in the demographics of testing. This was especially true in the early pandemic period, leading to under- surveillance and -reporting of COVID-19 cases in females especially, in those of younger and older age groups.

Omicron and Delta variant spike protein mutations comparison and their interaction with ACE2 receptor

The current outbreak of coronavirus-associated disease characterized as coronavirus disease 19 (COVID-19) marked its existence in late 2019. Since then, it has been a concern for human health and safety. Coronaviruses (CoVs) are known to cause a wide range of diseases;out of which common cold and pneumonia occur in human beings. In this review, we elaborate on the basic characteristics, structure, variants mutations and the pathological attributes of SARS-CoV 2. We also discuss the interaction of the viral proteins with the host cell receptor known as the ACE2 receptor and various therapeutics for the treatment of disease.

Factors associated with COVID-19-related mental health among Asian Indians in the United States.

Background: In the United States, the COVID-19 pandemic has caused increased mental health symptoms and mental illness. Specific subgroups such as Asian Indians in the US have also been subject to additional stressors due to unprecedented loss of lives in their home country and increased Asian hate due to the misperception that Asians are to be blamed for the spread of the SARS-CoV-2. Objective: We examined the various factors including discrimination associated with COVID-19-related mental health symptoms among Asian Indians. Methods: We administered an online survey between May 2021 and July 2021 using convenient and snowball sampling methods to recruit Asian Indian adults (age > 18 years, N = 289). The survey included questions on mental health and the experience with unfair treatment in day-to-day life. Descriptive analysis and logistic regressions were performed. Results: Overall, 46.0% reported feeling down, depressed, or lonely and feeling nervous, tense, or worried due to the COVID-19 pandemic; 90.0% had received at least one dose of vaccination and 74.7% reported some form of discrimination. In the fully-adjusted logistic regression, age (AOR = 0.95; 95%CI- 0.92, 0.97;p < 0.01) and general health (AOR=0.84; 95%CI- 0.73, 0.97; p < 0.015) were negatively associated with mental health symptoms. Participants who experienced discrimination were more likely (AOR=1.26; 95%CI- 1.08, 1.46; p < 0.01) to report mental health symptoms. Conclusion: In this highly vaccinated group of Asian Indians discriminatory behaviors were associated with mental health symptoms suggesting the need for novel institutional level policy responses to reduce anti-Asian racism.

COVID-19 Risk Perception and Prevention Practices among High- and Low-Density Populations in Bangladesh: A Mixed-Methods Study.

We aimed to explore coronavirus disease 2019 (COVID-19) risk perception and prevention practices among people living in high- and low-population density areas in Dhaka, Bangladesh. A total of 623 patients with confirmed COVID-19 agreed to participate in the survey. Additionally, we purposively selected 14 participants from diverse economic and occupational groups and conducted qualitative interviews for them accordingly. Approximately 70% of the respondents had low socioeconomic status. Among the 623 respondents, 146 were from low-density areas, and 477 were from high-density areas. The findings showed that study participants perceived COVID-19 as a punishment from the Almighty, especially for non-Muslims, and were not concerned about its severity. They also believed that coronavirus would not survive in hot temperatures or negatively impact Bangladeshis. This study revealed that people were reluctant to undergo COVID-19 testing. Family members hid if anyone tested positive for COVID-19 or did not adhere to institutional isolation. The findings showed that participants were not concerned about COVID-19 and believed that coronavirus would not have a devastating impact on Bangladeshis; thus, they were reluctant to follow prevention measures and undergo testing. Tailored interventions for specific targeted groups would be relevant in mitigating the prevailing misconceptions.

Identifying Diversity, Equity, Inclusion, and Accessibility (DEIA) Indicators for Transportation Systems using Social Media Data: The Case of New York City during Covid-19 Pandemic (preprint)

The adoption of transportation policies that prioritized highway expansion over public transportation has disproportionately impacted minorities and low-income people by restricting their access to social and economic opportunities and thus resulting in residential segregation. Policymakers, transportation researchers, planners, and practitioners have started acknowledging the need to build a diverse, equitable, inclusive, and accessible (DEIA) transportation system. Traditionally, this has been done through survey-based approaches that are time-consuming and expensive. While there is recent attention on leveraging social media data in transportation, the literature is inconclusive regarding the use of social media data as a viable alternative to traditional sources to identify the latent DEIA indicators based on public reactions and perspectives on social media. This study utilized large-scale Twitter data covering eight counties around the New York City (NYC) area during the initial phase of the Covid-19 lockdown to address this research gap. Natural language processing techniques were used to identify transportation-related major DEIA issues for residents living around NYC by analyzing their relevant tweet conversations. The study revealed that citizens, who had negative sentiments toward the DEIA of their local transportation system, broadly discussed racism, income, unemployment, gender, ride dependency, transportation modes, and dependent groups. Analyzing the socio-demographic information based on census tracts, the study also observed that areas with a higher percentage of low-income, female, Hispanic, and Latino populations share more concerns about transportation DEIA on Twitter.

Machine Learning Approaches for Predicting Suicidal Behaviors among University Students in Bangladesh during the COVID-19 Pandemic (preprint)

Background: Psychological and behavioral stresses increased enormously during the global COVID-19 pandemic. This study intends to identify the best machine learning model to forecast suicide risk among university students in Bangladesh. Methodology: An anonymous online survey utilizing DASS-21 and Insomnia Severity Index (ISI) to assess depression, anxiety, and stress levels; Suicidal Behaviors Questionnaire-Revised (SBQ-R) to identify suicidal risk was conducted from 1 to 30 June 2022. We compared six popular machine learning models (MLM), including Logistic Regression (LR), Support Vector Machine (SVM), Naïve Bayes (NB), Classification Tree (CT), and Random Forest (RF), to identify the most efficient predictive model for suicidal behavior through several metrics such as accuracy, Kappa, and receiver operating characteristic curve ( ROC). Result Determinants predicting suicidal behavior include depression, insomnia, anxiety, and stress. Besides, sex, relationship status, family income, loss of jobs, and death within the family from COVID-19 are crucial suicidal risk predictors. The performance evaluation and comparison of MLM show that all models behaved consistently and were comparable in predicting suicidal risk determinants since the ranges were for accuracy (0.76 to 0.79); Kappa (0.52 to 0.59); ROC (0.76 to 0.89); sensitivity (0.76 to 0.81), and specificity (0.72 to 0.82). SVM was the best and most consistent performing model among all MLM in terms of accuracy (79%), Kappa (0.59), ROC (0.89), sensitivity (0.81), and specificity (0.81). Conclusion SVM is the best MLM in identifying predictors of suicidal risk among university students to develop a screening tool that can guide policymakers and universities in designing appropriate, timely suicide prevention interventions.

The clinical features and estimated incidence of MIS-C in Cape Town, South Africa.

BACKGROUND: Multisystem inflammatory syndrome is a severe manifestation of SARS-CoV-2 in children. The incidence of MIS-C after infection is poorly understood. There are very few cohorts describing MIS-C in Africa despite MIS-C being more common in Black children worldwide. METHODS: A cohort of children with MIS-C and healthy children was recruited from May 2020 until May 2021 from the two main paediatric hospitals in Cape Town, South Africa. Clinical and demographic data were collected, and serum was tested for SARS-CoV-2 antibodies. The incidence of MIS-C was calculated using an estimation of population exposure from seroprevalence in the healthy group. Summary data, non-parametric comparisons and logistic regression analyses were performed. RESULTS: Sixty eight children with MIS-C were recruited with a median age of 7 years (3.6, 9.9). Ninety seven healthy children were recruited with a 30% seroprevalence. The estimated incidence of MIS-C was 22/100 000 exposures in the city in this time. Black children were over-represented in the MIS-C group (62% vs 37%, p = 0.002). The most common clinical features in MIS-C were fever (100%), tachycardia (98.5%), rash (85.3%), conjunctivitis (77.9%), abdominal pain (60.3%) and hypotension (60.3%). The median haemoglobin, sodium, neutrophil count, white cell count, CRP, ferritin, cardiac (pro-BNP, trop-T) and coagulation markers (D-dimer and fibrinogen) were markedly deranged in MIS-C. Cardiac, pulmonary, central nervous and renal organ systems were involved in 71%, 29.4%, 27.9% and 27.9% respectively. Ninety four percent received intravenous immune globulin, 64.7% received methylprednisolone and 61.7% received both. Forty percent required ICU admission, 38.2% required inotropic support, 38.2% required oxygen therapy, 11.8% required invasive ventilation and 6% required peritoneal dialysis. Older age was an independent predictor for the requirement for ionotropic support (OR = 1.523, CI 1.074, 2.16, p = 0.018). The median hospital stay duration was 7 days with no deaths. CONCLUSION: The lack of reports from Southern Africa does not reflect a lack of cases of MIS-C. MIS-C poses a significant burden to children in the region as long as the pandemic continues. MIS-C disproportionately affects black children. The clinical manifestations and outcomes of MIS-C in this region highlight the need for improved surveillance, reporting and data to inform diagnosis and treatment.

Studying structure of Coronaviridae, analyzing their geometry and focusing on the role of electronic applications in health awareness of viruses

Purpose: This study aims to focus on electronic applications that have an effective role in raising the awareness of the dangers of viruses' transmission from person-to-person and their positive and important impact on people's lives. Design/methodology/approach: The authors illustrated the effects of socializing with infected people on a human body by a model in geometry and how the prospected antibiotic annihilates the structure of the virus. The authors discussed vital operations inside the human body to expound the geometry of objects that are closed under their operations, such as viruses, especially Coronaviridae. Findings: Also, the authors discussed some of the e-health applications in Jordan. As e-health activities, programs and applications have been given attention, the authors focused on potentials for constructing strategies that lead to create a featuring health technology. Originality/value: Moreover, in this study, the authors explored the structure and geometry of Coronaviridae family, especially coronavirus that causes lots of diseases, and explained its movement mechanism using the mathematical structures. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Screening of personality profile and aggressive intent in pooled analysis of COVID-19 survivors - An Analytical, Cross-sectional Study

Background: A bidirectional relationship was seen between COVID 19 survivors and psychological issues. Global research shows 1 - 7% of patients infected with COVID had aggressive behaviour in acute as well as post illness stage. In general population, people with higher extroversion scores were associated with lesser social distancing, thereby high chances of infection. No clear data exists from India to comment on personality profile or aggressive intent among COVID survivors. Aim: The current study aimed to assess the personality profile and aggression intent among COVID-19 survivors in patients from Telangana. Methodology: This study is conducted in hospital out-patient or in-patient setting of KIMS, Narketpally, Nalgonda, Telangana in patients of COVID-19. A total of 157 COVID-19 patients were recruited based on convenient sampling. The data from patients was collected using standardized objective semi-structured proforma which contains clinical and sociodemographic profile, Big Five Inventory, Assessment of Aggressive Intent (which includes six components). Results: Among the study population, 18.5% of them had positive scores in one or more of the six components of aggression. On personality assessment, patients with aggression had significantly lower mean scores on agreeableness (p value 0.003) and significantly higher mean scores on neuroticism (p value 0.049). Conclusion: COVID survivors, along with medical complications, have a risk of having psychological disturbances like aggression. Clinicians should be aware and screen for these psychological issues when the patient comes for follow-up. Early intervention and management of aggression can help in improving the patient's quality of life.

Mental Health Consequences of Covid-19 among Health Care Workers in Abbottabad

Objective: To compare the mental health impact and Post Traumatic Stress Disorder between medical and paramedical staff using DASS-21 and IES scale respectively and to find association of mental impact of COVID-19 with socio-demographic variables. Study Design: Analytical cross sectional study Place and Duration of Study: This study was conducted at the Department of Medicine, Ayub Teaching Hospital Abbottabad for 16 months from June, 2020 to October, 2021. Materials and Methods: Carried out on 150 health care workers of Ayub Teaching Hospital. Data was collected by using two validated questionnaires DASS and IES scales. Analysis was conducted by SPSS version 20. Independent sample t test was used for comparison of scores between medical and paramedical staff while chi square test of association was used to find association of mental impact with socio-demographic variables. P value of ≤0.05 was considered significant. Results: The mean age of the health care workers was 30.01±6.62 years. Out of 150 participants, 105 (70%) were doctors, 45 (30%) were paramedics. Male to female ratio was 1:1. Overall mean depression score accounted for 8.81±8.26;anxiety score was 7.94±7.86;stress score was 12.60±9.02 and mean PTSD score was 24.76±16.40. A statistically significant difference was observed between medical and paramedical staff for stress (p=0.002) and PTSD (p=0.05). Stress was found to be significantly associated with category of health workers (p<0.001) while anxiety with gender (p=0.04). Conclusion: Substantial impact of COVID-19 on mental health of healthcare workers was found during Covid-19. © 2022 Medical Forum Monthly. All rights reserved.

SARS-CoV-2 Variants of Concern (VOC) Alpha, Beta, Gamma, Delta, and Omicron coincident with consecutive pandemic waves in Pakistan (preprint)

Identification and monitoring of SARS-CoV-2 Variants of Concern/Interest (VOC/VOIs) is essential to guide public health measures. We report the surveillance of VOCs circulating in Karachi during the pandemic between April 2021 and February 2022. We screened 2150 SARS-CoV-2 PCR positive samples received at the AKUH Clinical Laboratories. VOC was identified using a PCR-based approach targeting lineage-specific mutations using commercially available assays. Of the SARS-CoV-2 PCR positive samples, 81.7% had VOC/VOI, while 18.3% were undetermined. Alpha variants were predominant at 82.5% and 40.3% of the cases in April and May 2021. Beta variants increased in May (29%) and June (42%) and then reduced to 6% by July. Gamma variant cases were at 14.5% and 9% in May and June, respectively. Delta variants first detected in May, increased to comprise 66% of all variants by July, remaining dominant in August, September, October, and November 2021 at 88%, 91%, 91% and 85% respectively. Omicron (BA.1) variants emerged in December, rising to 42% of cases with an increase to 81% by January 2022 and then reducing to 45% in February 2022. Delta variant prevalence was coincident with increased hospital admissions and mortality. The Omicron variant surge was associated with increased daily infections but limited COVID-19 severity. We highlight the predominance of the VOCs identified through a rapid PCR based approach. As this is important to inform a public health response, we propose that a mutation targeted approach can be a rapid, lower cost solution to aid tracking of known VOCs during pandemic waves.

Transmission of SARS-CoV-2 in the Population Living in High- and Low-Density Gradient Areas in Dhaka, Bangladesh

Community transmission of SARS-CoV-2 in densely populated countries has been a topic of concern from the beginning of the pandemic. Evidence of community transmission of SARS-CoV-2 according to population density gradient and socio-economic status (SES) is limited. In June–September 2020, we conducted a descriptive longitudinal study to determine the community transmission of SARS-CoV-2 in high- and low-density areas in Dhaka city. The Secondary Attack Rate (SAR) was 10% in high-density areas compared to 20% in low-density areas. People with high SES had a significantly higher level of SARS-CoV-2-specific Immunoglobulin G (IgG) antibodies on study days 1 (p = 0.01) and 28 (p = 0.03) compared to those with low SES in high-density areas. In contrast, the levels of seropositivity of SARS-CoV-2-specific Immunoglobulin M (IgM) were comparable (p > 0.05) in people with high and low SES on both study days 1 and 28 in both high- and low-density areas. Due to the similar household size, no differences in the seropositivity rates depending on the population gradient were observed. However, people with high SES showed higher seroconversion rates compared to people with low SES. As no difference was observed based on population density, the SES might play a role in SARS-CoV-2 transmission, an issue that calls for further in-depth studies to better understand the community transmission of SARS-CoV-2.