Community Transmission Of COVID-19 Research Articles

Knowledge, Perception, and Attitudes of Residents of Northern Region of Ghana Towards COVID-19

Background: Africa is gradually becoming an epicenter of the COVID-19 pandemic. Based on the current disease trend, Africa might be the last hardest-hit continent. While scientific investigations continue to develop effective management through medications and vaccines, existing knowledge, perceptions, and attitudes could be harnessed to develop an effective strategy to curb community transmission of COVID-19. The present study assessed the awareness level, perceptions, and attitudes of people living in rural, peri-urban, and urban communities in Northern Ghana and their preparedness for the prevention and containment of COVID-19. Methods: We conducted a face-to-face interview and administered 553 semi-structured questionnaires in 18 rural, peri-urban, and urban communities in Tolon District, Kumbungu District, Sagnarigu Municipality, Savelugu Municipality, and Tamale Metropolis from April 23 to June 8, 2020. Results: The percentages of males and females among the respondents were 56.8% and 43.2%, respectively. Nearly half (41%) of the respondents had no formal education, and 91.3% of them were Muslims. Most respondents (85%) believed that COVID-19 is a punishment from God. There was a significant difference (P<0.001) between the first-time rural, peri-urban, and urban communities heard of COVID-19. The majority (63%) of the rural respondents depended on radio, while the peri-urban and urban respondents (51%) relied on TV for information on COVID-19. All respondents were aware of COVID-19, and 91.7% could mention at least two symptoms of the disease. However, 18% believed there was no COVID-19 in Ghana. Most respondents (69.6%) thought they would not contract the virus. Conclusion: Our findings may provide valuable data to the government and other stakeholders to control COVID-19.

Surge Capacity of Taipei's Regional Emergency Medical System during COVID-19: A System Dynamics Approach.

The community transmission of COVID-19 has caused the breakdown of the regional emergency medical system (REMS), impacting the rights and care of regional patients with acute and severe conditions. This study proposes a model for the surge capacity of REMS to plan for readiness and preparedness during challenging events that overload capacity. The surge capacity of REMS during the COVID-19 pandemic was studied. The data collection included 26 hospitals that received the data. To simulate the dynamics of Taipei's REMS surge capacity, we observed its ability to treat COVID-19 patients with moderate to severe acute respiratory distress syndrome (ARDS). This will involve monitoring the stock of ventilators, physicians, and nurses within the subsystem loops. Healthcare managers and administrators can use the overload model and hypothetical scenarios to develop new scenarios with different demands on surge capacity. The REMS system capacity model can be used as an aid to guide planning and cross-checking for address Prepare to plan. We combined data regarding the availability of ventilators, physicians, nurses, specialized beds, and general acute care beds in our simulations. Thus, our simulations, with support from a well-established regional command and management structure, could help REMS achieve the optimal surge capacity.

The impact of the cruise ship coral princess on COVID-19 transmission in regional Western Australia in 2022.

Increased COVID-19 community transmission in regional areas with high Aboriginal populations, limited health infrastructure and low vaccination rates could result in clusters of transmission with increased deaths rates. Pilbara, a regional community with a high Aboriginal population, showed a 34.8% increase in COVID-19 cases in the 4-week post-cruise-ship docking.

How Ho Chi Minh City adapted its care pathway to manage the first large-scale community transmission of COVID-19

Ho Chi Minh City, Viet Nam undertook a series of measures in response to the fourth and largest wave of COVID-19. The care pathway was continuously reconfigured through leadership from all levels of government and engagement of the community. This resulted in a shift towards integrated severity-based care consisting of multiple levels of health-care facilities and home care. This flexible approach based on the rapidly changing local context enabled Ho Chi Minh City to limit the extent to which health-care capacity was overwhelmed.

"Be honest and gain trust": a population health study to understand the factors associated with building trust in local government related to COVID-19 and vaccination in three historically disinvested neighborhoods in New York City.

Distrust in government among people of color is a response to generations of systemic racism that have produced preventable health inequities. Higher levels of trust in government are associated with better adherence to government guidelines and policies during emergencies, but factors associated with trust and potential actions to increase trust in local government are not well understood. The COVID-19 Community Recovery study sampled participants from the New York City (NYC) Department of Health and Mental Hygiene's NYC Health Panel, a probability-based survey panel who complete health surveys periodically. Participants who lived in one of three historically disinvested communities in NYC where the NYC Department of Health and Mental Hygiene has dedicated resources to reduce health inequities were included. The cross-sectional survey was fielded from September 30 to November 4, 2021 and could be self-administered online or conducted via CATI (Computer Assisted Telephone Interviewing) in English, Spanish, and Simplified Chinese (Mandarin and Cantonese by phone). Demographic data were summarized by descriptive statistics. Crude and adjusted logistic regression analyses were used to assess factors predictive of trust in local government as a source of information about COVID-19 vaccines. Open-ended responses about strengthening residents' trust in local government were coded using an iteratively generated codebook. In total, 46% of respondents indicated NYC local government was a trusted source of information about COVID-19 vaccines, relatively high compared to other sources. In bivariate analyses, race/ethnicity, age group, educational attainment, length of time living in NYC, and household income were significantly associated with identifying NYC government as a trusted source of information about COVID-19 vaccines. In multivariable logistic regression, no variables remained significant predictors of selecting local government as a trusted source of information. Key recommendations for local government agencies to build residents' trust include communicating clearly and honestly, addressing socioeconomic challenges, and enhancing public COVID-19 protection measures. Study findings demonstrate that nearly half of residents in three historically divested NYC communities consider local government to be a trusted source of information about COVID-19 vaccines. Strategies to increase trust in local government can help reduce community transmission of COVID-19 and protect public health.

Estimation of SARS-CoV-2 Seroprevalence in Central North Carolina: Accounting for Outcome Misclassification in Complex Sample Designs.

Population-based seroprevalence studies are crucial to understand community transmission of COVID-19 and guide responses to the pandemic. Seroprevalence is typically measured from diagnostic tests with imperfect sensitivity and specificity. Failing to account for measurement error can lead to biased estimates of seroprevalence. Methods to adjust seroprevalence estimates for the sensitivity and specificity of the diagnostic test have largely focused on estimation in the context of convenience sampling. Many existing methods are inappropriate when data are collected using a complex sample design. We present methods for seroprevalence point estimation and confidence interval construction that account for imperfect test performance for use with complex sample data. We apply these methods to data from the Chatham County COVID-19 Cohort (C4), a longitudinal seroprevalence study conducted in central North Carolina. Using simulations, we evaluate bias and confidence interval coverage for the proposed estimator compared with a standard estimator under a stratified, three-stage cluster sample design. We obtained estimates of seroprevalence and corresponding confidence intervals for the C4 study. SARS-CoV-2 seroprevalence increased rapidly from 10.4% in January to 95.6% in July 2021 in Chatham County, North Carolina. In simulation, the proposed estimator demonstrates desirable confidence interval coverage and minimal bias under a wide range of scenarios. We propose a straightforward method for producing valid estimates and confidence intervals when data are based on a complex sample design. The method can be applied to estimate the prevalence of other infections when estimates of test sensitivity and specificity are available.

Impact on mental health due to COVID-19 pandemic: A cross-sectional study in Bangladesh

The government of Bangladesh has implemented the “Stay Home” policy following the WHO recommendation to resist the community transmission of Covid-19. As a result, the routine activities of all government, semi-government establishments, including educational institutions, are severely affected, and the country's economic growth becomes slowed down. To overcome such a situation, the relevant authorities have introduced the “Work from Home” policy for the employees and “Remote Education” for students. However, due to the persistence of multi-dimensional socio-economic problems, many employees and students face big challenges in performing their regular jobs while adopting such a policy. Consequently, enormous psychological anxiety has been developed for all people, including students, parents, employees, etc., and concurrently created severe changes in their behavior. This study aims to analyze the reasons for the behavioral changes of the employees, students, academic staff, and family members of different ages due to psychological anxiety, stress, or physical issues. A comprehensive online-based survey has been carried out on people working in various sectors in Bangladesh. A modified Apriori Algorithm has been used to sort out the associations between the causes and types of behavioral changes. Analyzed data revealed a massive human behavioral change in most participants. This finding indicates that the negligence of those significant human behavioral changes may cause a higher risk of creating psychological imbalance. Therefore, there is a need to have a solid understanding of the reasons for the behavioral changes and set up standard guidelines to maintain “Work from Home” in this Covid-19 situation to avoid psychological imbalance. Based on this study, some suggestions have been given for implementation by the government on an urgent basis.

Cohort Profile: Virus Watch-understanding community incidence, symptom profiles and transmission of COVID-19 in relation to population movement and behaviour.

Cohort Profile: Virus Watch-understanding community incidence, symptom profiles and transmission of COVID-19 in relation to population movement and behaviour.

Utilizing data to foster equity in infection prevention outreach among skilled nursing facilities in Michigan

Background: Since October 2020, the Infection Prevention Resource and Assessment Team (IPRAT) has provided infection prevention guidance and support to congregate-care settings throughout Michigan. Specifically, outreach to skilled nursing facilities (SNFs) in response to reported positive COVID-19 resident and staff cases. Case rates provide limited data and do not factor in additional variables, such as staffing shortages, geographical location, or access to supplies, which can increase the vulnerability of staff and residents to outbreaks. To facilitate equitable outreach, a risk assessment was developed using variables related to infection prevention and poor COVID-19 outcomes utilizing local, state, and federal data reporting websites. Methods: A retrospective data review of IPRAT’s electronic data repository was performed, and 2 distinct periods were identified between November 6, 2020, and December 5, 2022. Outreach method 1 involved only using case counts from November 6, 2020, to September 24, 2021. Outreach method 2 (new risk-assessment–based outreach) involved additional data points from April 12, 2021, to December 5, 2022. Data included 17 self-reported items from the NHSN, 3 characteristics regarding facilities’ COVID-19 units, and 7 community-level variables derived from county vaccine rates, social vulnerability index (SVI), and COVID-19 community transmission level. The scoring of each data point ranged from 0–10, and outreach was prioritized to facilities with the highest overall scores. Successful referrals (resulting in a site visit) were compared to the SVI and healthcare emergency regional maps to determine whether the new outreach method reached more facilities in vulnerable communities. Results: Of 358 outreach attempts, IPRAT had a higher success rate with method 2 (6.9%) compared to method 1 (5.3%) and improved outreach in rural Michigan regions 7 and 8 (15% vs 3%). Site visits in counties with a high SVI rating with method 2 were 14.5% versus 10.6% using method 1. COVID-19 prevention referral success rates were higher (4.4% vs 3.1%) using method 2. Conclusions: The risk-assessment–based outreach method showed improvement in overall referral success rates among facilities in rural and higher-SVI counties. These communities tend to experience higher health disparities and poorer health outcomes. Incorporating the more nuanced data variables correlated with at-risk congregate-care settings receiving timelier outreach. The limitations of the study include sample size, period of data collected (2 years), and the complexity of objectively measuring equity.Disclosures: None

Epidemiological intelligence community network intervention: a community response for COVID-19 community transmission

BackgroundExpanding and providing access to early detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) through testing community-based strategies among socially vulnerable communities (SVC) are critical to reducing health disparities. The Epidemiological Intelligence Community Network (EpI-Net) community-based intervention sought to increase coronavirus 2019 (COVID-19) testing uptake and prevention practices among SVC in Puerto Rico (PR). We evaluated EpI-Net’s community leaders’ capacity-building component by assessing pre-post COVID-19 public health workshops’ tests’ score changes and satisfaction among trained community leaders.MethodsA total of 24 community leaders from SVC in PR have completed four community workshops. Pre- and post-assessments were completed as part of the health promotors training program to evaluate participants’ tests score changes and satisfaction outcomes.ResultsPreliminary results showed: (1) high intervention retention levels of community leaders (85.7% acceptance rate); (2) change in post-test scores for community engagement strategies (p = 0.012); (3) change in post-test educational scores in COVID-19 prevention practices (p = 0.014); and (4) a change in scores in public health emergency management strategies (p < 0.001).ConclusionsThe overall workshop satisfaction was 99.6%. Community leaders have shown the importance of community capacity building as a key component for intervention feasibility and impact.Trial registrationOur study was retrospectively registered under the ClinicalTrial.gov ID NCT04910542.

Epidemiological characteristics of seasonal influenza under implementation of zero-COVID-19 strategy in China

ObjectiveRespiratory viral diseases have posed a persistent threat to public health due to their high transmissibility. Influenza virus and SARS-Cov-2 are both respiratory viruses that have caused global pandemics. A zero-COVID-19 strategy is a public health policy imposed to stop community transmission of COVID-19 as soon as it is detected. In this study, we aim to examine the epidemiological characteristics of seasonal influenza in the past five years before and after the emergence of COVID-19 in China and observe the possible impact of the strategy on influenza. MethodsData from two data sources were retrospectively analyzed. A comparison on influenza incidence rate between Hubei and Zhejiang provinces was conducted based on data from the Chinese Center for Disease Control and Prevention (CDC). Then a descriptive and comparative analysis on seasonal influenza based on data from Zhongnan Hospital of Wuhan University and Hangzhou Ninth People`s Hospital before and after the outbreak of SARS-CoV-2 was conducted. ResultsFrom 2010–2017, both provinces experienced relatively low influenza activity until the 1st week of 2018, when they reached peak incidence rates of 78.16/100000PY, 34.05/100000PY respectively. Since then, influenza showed an obvious seasonality in Hubei and Zhejiang until the onset of COVID-19. During 2020 and 2021, there was a dramatic decline in influenza activity compared to 2018 and 2019. However, influenza activity seemed to rebound at the beginning of 2022 and surged in summer, with positive rates of 20.52% and 31.53% in Zhongnan Hospital of Wuhan University and Hangzhou Ninth People`s Hospital respectively as of the time writing this article. ConclusionsOur results reinforce the hypothesis that zero-COVID-19 strategy may impact the epidemiological pattern of influenza. Under the complex pandemic situation, implementation of NPIs could be a beneficial strategy containing not only COVID-19 but also influenza.

Wastewater Surveillance Can Function as an Early Warning System for COVID-19 in Low-Incidence Settings

During the first two years of the COVID-19 pandemic, Australia implemented a series of international and interstate border restrictions. The state of Queensland experienced limited COVID-19 transmission and relied on lockdowns to stem any emerging COVID-19 outbreaks. However, early detection of new outbreaks was difficult. In this paper, we describe the wastewater surveillance program for SARS-CoV-2 in Queensland, Australia, and report two case studies in which we aimed to assess the potential for this program to provide early warning of new community transmission of COVID-19. Both case studies involved clusters of localised transmission, one originating in a Brisbane suburb (Brisbane Inner West) in July-August 2021, and the other originating in Cairns, North Queensland in February-March 2021. Publicly available COVID-19 case data derived from the notifiable conditions (NoCs) registry from the Queensland Health data portal were cleaned and merged spatially with the wastewater surveillance data using statistical area 2 (SA2) codes. The positive predictive value and negative predictive value of wastewater detection for predicting the presence of COVID-19 reported cases were calculated for the two case study sites. Early warnings for local transmission of SARS-CoV-2 through wastewater surveillance were noted in both the Brisbane Inner West cluster and the Cairns cluster. The positive predictive value of wastewater detection for the presence of notified cases of COVID-19 in Brisbane Inner West and Cairns were 71.4% and 50%, respectively. The negative predictive value for Brisbane Inner West and Cairns were 94.7% and 100%, respectively. Our findings highlight the utility of wastewater surveillance as an early warning tool in low COVID-19 transmission settings.

High SARS-CoV-2 infection rates and viral loads in community-dwelling individuals from rural indigenous and mestizo communities from the Andes during the first wave of the COVID-19 pandemic in Ecuador.

Neglected indigenous groups and underserved rural populations in Latin America are highly vulnerable to COVID-19 due to poor health infrastructure and limited access to SARS-CoV-2 diagnosis. The Andean region in Ecuador includes a large number of isolated rural mestizo and indigenous communities living under poverty conditions. We herein present a retrospective analysis of the surveillance SARS-CoV-2 testing in community-dwelling populations from four provinces in the Ecuadorian Andes, carried out during the first weeks after the national lockdown was lifted in June 2020. A total number of 1,021 people were tested for SARS-CoV-2 by RT-qPCR, resulting in an overall high infection rate of 26.2% (268/1,021, 95% CI: 23.6-29%), which was over 50% in several communities. Interestingly, community-dwelling super spreaders with viral loads over 108 copies/mL represented 7.46% (20/268, 95% CI: 4.8-11.1%) of the SARS-CoV-2 infected population. These results support that COVID-19 community transmission in rural communities from the Andean region was happening at the early stages of the COVID-19 pandemic in Ecuador and point out the weakness of the COVID-19 control program. Community-dwelling individuals in neglected rural and indigenous communities should be considered for a successful control and surveillance program in future pandemics in low- and middle-income countries.

1902. Whole Genome Sequence analysis of early community transmission SARS-CoV-2 samples in the Philippines

Abstract Background The Philippines has recorded nearly 3.7 million COVID-19 cases and more than 60,000 deaths. The first three cases of COVID-19 in the country were reported in January 2020 (1 lineage A, 2 lineage B, all Chinese tourists), with the first death outside China occurring among these cases. No cases were reported in February 2020. The first Filipino cases were reported March 2020. With over one million overseas Filipinos repatriated, tracking the introduction of waves of variants and subsequent community spread is important in order to improve future control efforts. Methods We analyzed 35 archived samples collected from March to September 2020 at the Philippines National Institutes of Health. SARS-CoV2 RT-PCR positive samples with Ct values from 15 to 25 were sequenced using Illumina HiSeq and analyzed using an in-house bioinformatics pipeline. Lineages were assigned using PANGOLIN. 14 whole genome sequences were generated with sufficient coverage. These were analyzed with 439 whole genome sequences from February to September 2020 that were publicly available on ViruSurf and GISAID to generate transmission maps. Results Transmission maps are shown in Figure 1. The earliest community transmission of COVID-19 in the Philippines was from lineage B.6 in March 2020 most closely related to B.6 from India. There is no evidence of onward transmission from the initial reported cases in January 2020 (lineage A and B). In June 2020, the predominant lineage switched to B.1 and its sublineages from Europe, coincident with a surge in cases. Figure 1.Alignment of the whole genome sequences from early Philippine samples and related SARS-COV2 sequences from ViruSurf and GISAID. Conclusion Transmission maps are shown in Figure 1. The earliest community transmission of COVID-19 in the Philippines was from lineage B.6 in March 2020 most closely related to B.6 from India. There is no evidence of onward transmission from the initial reported cases in January 2020 (lineage A and B). In June 2020, the predominant lineage switched to B.1 and its sublineages from Europe, coincident with a surge in cases. Disclosures Edsel Maurice Salvana, MD, MSD: Advisor/Consultant|MSD: Honoraria|Pfizer: Advisor/Consultant|Pfizer: Honoraria.

Characteristics, treatment outcomes and experiences of COVID-19 patients under home-based care in Kapelebyong district in Uganda: a mixed-methods study

BackgroundA rapid increase in community transmission of COVID-19 across the country overwhelmed Uganda’s health care system. In response, the Ministry of Health adopted the home-based care strategy for COVID-19 patients with mild-to-moderate disease. We determined the characteristics, treatment outcomes and experiences of COVID-19 patients under home-based care during the second wave in Kapelebyong district, in eastern Uganda.MethodsWe conducted a sequential explanatory mixed-methods study. We first collected quantitative data using an interviewer-administered questionnaire to determine characteristics and treatment outcomes of COVID-19 patients under home-based care. Cured at home was coded as 1 (considered a good outcome) while being admitted to a health facility and/or dying were coded as 0 (considered poor outcomes). Thereafter, we conducted 11 in-depth interviews to explore the experiences of COVID-19 patients under home-based care. Multivariable logistic regression was used to assess factors associated with poor treatment outcomes using Stata v.15.0. Thematic content analysis was used to explore lived experiences of COVID-19 patients under home-based care using NVivo 12.0.0ResultsA total of 303 study participants were included. The mean age ± standard deviation of participants was 32.2 years ± 19.9. Majority of the participants [96.0% (289/303)] cured at home, 3.3% (10/303) were admitted to a health facility and 0.7% (2/303) died. Patients above 60 years of age had 17.4 times the odds of having poor treatment outcomes compared to those below 60 years of age (adjusted odds ratio (AOR): 17.4; 95% CI: 2.2–137.6). Patients who spent more than one month under home-based care had 15.3 times the odds of having poor treatment outcomes compared to those that spent less than one month (AOR: 15.3; 95% CI: 1.6–145.7). From the qualitative interviews, participants identified stigma, fear, anxiety, rejection, not being followed up by health workers and economic loss as negative experiences encountered during home-based care. Positive lived experiences included closeness to friends and family, more freedom, and easy access to food.ConclusionHome-based care of COVID-19 was operational in eastern Uganda. Older age (> 60 years) and prolonged illness (> 1 months) were associated with poor treatment outcomes. Social support was an impetus for home-based care.

Protocol for a winter sentinel surveillance program of notifiable respiratory viruses in Queensland.

With the reduction in access to polymerase chain reaction (PCR) testing and changes in testing guidelines in Australia, a reduced number of people are seeking testing for coronavirus disease (COVID-19), limiting the opportunity to monitor disease transmission. Knowledge of community transmission of COVID-19 and other respiratory viruses is essential to better predict subsequent surges in cases during the pandemic to alert health services, protect vulnerable populations and enhance public health measures. We describe a methodology for a testing-based sentinel surveillance program to monitor disease in the community for early signal detection of SARS-CoV-2 and other respiratory viruses. A longitudinal active testing-based sentinel surveillance program for respiratory viruses (including SARS-CoV-2, influenza A, influenza B and Respiratory Syncytial Virus) will be implemented in some regions of Queensland. Adults will be eligible for enrolment if they are part of specific community groups at increased risk of exposure and have not had a COVID-19 infection in the last 13 weeks. Recruitment via workplaces will occur in-person, via email and through online advertisement. Asymptomatic participants will be tested via PCR for SARS-CoV-2 infection by weekly self-collected nasal swabs. In addition, symptomatic participants will be asked to seek SARS-CoV-2 and additional respiratory virus PCR testing at nominated COVID-19 testing sites. SARS-CoV-2 and respiratory virus prevalence data will be analysed weekly and at the end of the study period. Once implemented, this surveillance program will determine the weekly prevalence of COVID-19 and other respiratory viruses in the broader community by testing a representative sample of adults, with an aim to detect early changes in the baseline positivity rate. This information is essential to define the epidemiology of SARS-CoV-2 in the community in near-real time to inform public health control measures and prepare health services and other stakeholders for a rise in service demand.

Inborn errors of metabolism refuse to stay-at-home: Experiences of a state-wide biochemical genetics service during the COVID-19 pandemic.

The New South Wales (NSW) biochemical genetics (BG) service in Australia developed business continuity plans (BCPs) in response to the COVID-19 pandemic to ensure the essential service remained operational. This article aims to discuss the effects of the COVID-19 BCPs on the NSW BG service and patient care. BCPs were developed that included charting of NSW BG service workflow and services against staff resources and clinical impact on patients. The effect of the BCPs was analysed quantitatively by reviewing key performance indicators (result turnaround time, frequency and severity of clinical incidents and laboratory nonconformities) and qualitatively from staff feedback generated by a BG laboratory-wide survey. Alternative BCPs were implemented during the pre-defined period March 2020 to November 2021 (inclusive), to reflect changes in COVID-19 community transmission, vaccination rates; and health orders. Operation of our essential pathology service was maintained, with no significant difference observed in key performance indicators when compared to pre-COVID. During the pre-defined period of the COVID-19 pandemic, staff reported increased levels of both work- and out-of-work-related stress. The successful continuation of the BG service, with no statistically significant impact on patient care and delivery of essential services, can be attributed to strategic planning and timely implementation of these BCPs. In conjunction with the resilient and robust attitude of the staff during this ever-changing situation, this experience has served as an invaluable tool for future disaster management planning.

Use of interrupted Time Series Design in COVID-19 data of Nepal

Introduction: Nepal was hit hard by COVID-19 pandemic and is still struggling with its implications for individuals, societies, and health systems. We applied Interrupted Time Series (ITS) analysis to see if the government's decision to end two nationwide lockdowns had an impact on the average daily new cases of COVID-19 reported in Nepal.&#x0D; &#x0D; Method: ITS analysis on daily new cases of COVID-19 was performed for first and second nationwide lockdown on data of Nepal from data depository for 2019 Novel Coronavirus Visual Dashboard operated by Johns Hopkins University Center for Systems Science and Engineering. Impact of ''ending nationwide lockdown'' and possible associated factors were investigated.&#x0D; Result: The impact of removing first nationwide lockdown contributed to statistically significant rise of an average difference of 899 daily new cases due to community transmission of COVID-19. During second lockdown, even after imposing lockdown, cases overwhelmed existing healthcare system due to high infectivity of new Delta variant followed by a lack of adherence to public health measures and delayed decision to impose lockdown due to economic reasons. Whereas significant decline of cases was observed with an average difference of 2970 daily new cases after ending second nationwide lockdown mostly due to vaccine acceptance.&#x0D; &#x0D; Conclusion: First lockdown was imposed early due to uncertainty about progression of disease, curative measures and unavailability of vaccines. Ending of first lockdown was done untimely due to economic reasons and festive seasons. The unusual decline in cases after ending second lockdown could be contributed to increased vaccination in the country.&#x0D;

Identification of a rare SARS-CoV-2 XL hybrid variant in wastewater and the subsequent discovery of two infected individuals in Nevada

The identification of novel SARS-CoV-2 variants can predict new patterns of COVID-19 community transmission and lead to the deployment of public health resources. However, increased access to at-home antigen tests and reduced free PCR tests have recently led to data gaps for the surveillance of evolving SARS-CoV-2 variants. To overcome such limitations, we asked whether wastewater surveillance could be leveraged to detect rare variants circulating in a community before local detection in human cases. Here, we performed whole genome sequencing (WGS) of SARS-CoV-2 from a wastewater treatment plant serving Las Vegas, Nevada in April 2022. Using metrics that exceeded 100× depth at a coverage of >90 % of the viral genome, we identified a variant profile similar to the XL recombinant lineage containing 26 mutations found in BA.1 and BA.2 and three private mutations. Prompted by the discovery of this rare lineage in wastewater, we analyzed clinical COVID-19 sequencing data from Southern Nevada and identified two cases infected with the XL lineage. Taken together, our data highlight how wastewater genome sequencing data can be used to discover rare SARS-CoV-2 lineages in a community and complement local public health surveillance.

Contact tracing reveals community transmission of COVID-19 in New York City

Understanding SARS-CoV-2 transmission within and among communities is critical for tailoring public health policies to local context. However, analysis of community transmission is challenging due to a lack of high-resolution surveillance and testing data. Here, using contact tracing records for 644,029 cases and their contacts in New York City during the second pandemic wave, we provide a detailed characterization of the operational performance of contact tracing and reconstruct exposure and transmission networks at individual and ZIP code scales. We find considerable heterogeneity in reported close contacts and secondary infections and evidence of extensive transmission across ZIP code areas. Our analysis reveals the spatial pattern of SARS-CoV-2 spread and communities that are tightly interconnected by exposure and transmission. We find that locations with higher vaccination coverage and lower numbers of visitors to points-of-interest had reduced within- and cross-ZIP code transmission events, highlighting potential measures for curtailing SARS-CoV-2 spread in urban settings.