Age-Stratified Model to Assess Health Outcomes of COVID-19 Vaccination Strategies, Ghana.

We assessed the effect of various COVID-19 vaccination strategies on health outcomes in Ghana by using an age-stratified compartmental model. We stratified the population into 3 age groups: <25 years, 25-64 years, and ≥65 years. We explored 5 vaccination optimization scenarios using 2 contact matrices, assuming that 1 million persons could be vaccinated in either 3 or 6 months. We assessed these vaccine optimization strategies for the initial strain, followed by a sensitivity analysis for the Delta variant. We found that vaccinating persons <25 years of age was associated with the lowest cumulative infections for the main matrix, for both the initial strain and the Delta variant. Prioritizing the elderly (≥65 years of age) was associated with the lowest cumulative deaths for both strains in all scenarios. The consensus between the findings of both contact matrices depended on the vaccine rollout period and the objective of the vaccination program.

The use of digital technology to improve and monitor handwashing among children 12 years or younger in educational settings: a scoping review.

Our scoping review aimed to identify and describe the application of digital technology in hand hygiene research among children in educational settings. We searched for articles in PubMed, IEEE Xplore, and Web of Science. Original hand hygiene research with a form of digital technology used among children ≤12 years in educational settings was eligible for inclusion. Twelve studies met the eligibility criteria and the data were extracted by two teams of independent co-authors for narrative synthesis. Ten studies used digital technology as an intervention tool and two for monitoring purposes. Three main digital technologies were identified including computer games (n = 2), videos (n = 8), and video cameras (n = 2). Digital technologies found in our scoping review were reported to be effective in hand hygiene studies over short temporal periods especially when used in combination with other measures. Future research may demonstrate the effectiveness of digital technology in helping children develop sustainable handwashing behaviors.

Community Characteristics and COVID-19 Outcomes: A Study of 159 Counties in Georgia, United States.

BACKGROUND: The COVID-19 pandemic affects population groups differently, worsening existing social, economic, and health inequities. PURPOSE: This study examined 159 counties within Georgia to identify community characteristics associated with county-level COVID-19 case, hospitalization, and death rates. METHODS: Data from the 2020 County Health Rankings, the 2010 US Census, and the Georgia Department of Public Health COVID-19 Daily Status Report were linked using county Federal Information Processing Standard codes and evaluated through multivariable linear regression models. RESULTS: The percentages of children in poverty, severe housing problems, and people not proficient in the English language were significant predictors associated with increases in case, hospitalization, and death rates. Diabetic prevalence was significantly associated with increases in the hospitalization and death rates; in contrast, the percentages of people with excessive drinking and female were inversely associated with hospitalization and death rates. Other independent variables showing an association with death rate included the percentages of people reporting fair or poor health and American Indian/Alaska Native. IMPLICATION: Local authorities' proper allocation of resources and plans to address community social determinants of health are essential to mitigate disease transmission and reduce hospitalizations and deaths associated with COVID-19, especially among vulnerable groups.

Association Between Earthquake Exposures and Mental Health Outcomes in Phulpingdanda Village After the 2015 Nepal Earthquakes.

In 2015, two strong earthquakes, as well as continuous, high magnitude aftershocks, struck Nepal. Phulpingdanda village was greatly impacted due to its lack of infrastructure and environmental remoteness. Adults from sampled households were surveyed 1-year later to examine the association between earthquake exposures and indicators of depression, post-traumatic stress disorder (PTSD), and resilience. Results showed 33% of surveyed residents screened positive for depression, 9% screened positive for severe PTSD, and 46% displayed moderate to high resilience. Additionally, participants experienced resource loss (100%), damaged home and goods (99%), and exposure to the grotesque (82%). Traumatic earthquake experiences related to personal harm were associated with symptoms of depression and PTSD and resource loss was associated with depressive symptoms. Earthquake experiences associated with less damage to home and goods, but greater exposure to the grotesque were associated with increased resilience. This research adds to our knowledge of the relationship between traumatic exposures and indicators of psychological distress and resilience following a disaster.

Online surveillance of media health event reporting in Nepal: digital disease detection from a One Health perspective.

BACKGROUND: Traditional media and the internet are crucial sources of health information. Media can significantly shape public opinion, knowledge and understanding of emerging and endemic health threats. As digital communication rapidly progresses, local access and dissemination of health information contribute significantly to global disease detection and reporting. METHODS: Health event reports in Nepal (October 2013-December 2014) were used to characterize Nepal's media environment from a One Health perspective using HealthMap - a global online disease surveillance and mapping tool. Event variables (location, media source type, disease or risk factor of interest, and affected species) were extracted from HealthMap. RESULTS: A total of 179 health reports were captured from various sources including newspapers, inter-government agency bulletins, individual reports, and trade websites, yielding 108 (60%) unique articles. Human health events were reported most often (n = 85; 79%), followed by animal health events (n = 23; 21%), with no reports focused solely on environmental health. CONCLUSIONS: By expanding event coverage across all of the health sectors, media in developing countries could play a crucial role in national risk communication efforts and could enhance early warning systems for disasters and disease outbreaks.

Capacity building efforts and perceptions for wildlife surveillance to detect zoonotic pathogens: comparing stakeholder perspectives.

BACKGROUND: The capacity to conduct zoonotic pathogen surveillance in wildlife is critical for the recognition and identification of emerging health threats. The PREDICT project, a component of United States Agency for International Development's Emerging Pandemic Threats program, has introduced capacity building efforts to increase zoonotic pathogen surveillance in wildlife in global 'hot spot' regions where zoonotic disease emergence is likely to occur. Understanding priorities, challenges, and opportunities from the perspectives of the stakeholders is a key component of any successful capacity building program. METHODS: A survey was administered to wildlife officials and to PREDICT-implementing in-country project scientists in 16 participating countries in order to identify similarities and differences in perspectives between the groups regarding capacity needs for zoonotic pathogen surveillance in wildlife. RESULTS: Both stakeholder groups identified some human-animal interfaces (i.e. areas of high contact between wildlife and humans with the potential risk for disease transmission), such as hunting and markets, as important for ongoing targeting of wildlife surveillance. Similarly, findings regarding challenges across stakeholder groups showed some agreement in that a lack of sustainable funding across regions was the greatest challenge for conducting wildlife surveillance for zoonotic pathogens (wildlife officials: 96% and project scientists: 81%). However, the opportunity for improving zoonotic pathogen surveillance capacity identified most frequently by wildlife officials as important was increasing communication or coordination among agencies, sectors, or regions (100% of wildlife officials), whereas the most frequent opportunities identified as important by project scientists were increasing human capacity, increasing laboratory capacity, and the growing interest or awareness regarding wildlife disease or surveillance programs (all identified by 69% of project scientists). CONCLUSIONS: A One Health approach to capacity building applied at local and global scales will have the greatest impact on improving zoonotic pathogen surveillance in wildlife. This approach will involve increasing communication and cooperation across ministries and sectors so that experts and stakeholders work together to identify and mitigate surveillance gaps. Over time, this transdisciplinary approach to capacity building will help overcome existing challenges and promote efficient targeting of high risk interfaces for zoonotic pathogen transmission.

Modeling the health impact of increasing vaccine coverage and nonpharmaceutical interventions against coronavirus disease 2019 in Ghana.

Seroprevalence studies assessing community exposure to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Ghana concluded that population-level immunity remained low as of February 2021. Thus, it is important to demonstrate how increasing vaccine coverage reduces the economic and public health impacts associated with SARS-CoV-2 transmission. To that end, this study used a Susceptible-Exposed-Presymptomatic-Symptomatic-Asymptomatic-Recovered-Dead-Vaccinated compartmental model to simulate coronavirus disease 2019 (COVID-19) transmission and the role of public health interventions in Ghana. The impact of increasing vaccination rates and decline in transmission rates due to nonpharmaceutical interventions (NPIs) on cumulative infections and deaths averted was explored under different scenarios. Latin hypercube sampling-partial rank correlation coefficient (LHS-PRCC) was used to investigate the uncertainty and sensitivity of the outcomes to the parameters. Simulation results suggest that increasing the vaccination rate to achieve 50% coverage was associated with almost 60,000 deaths and 25 million infections averted. In comparison, a 50% decrease in the transmission coefficient was associated with the prevention of about 150,000 deaths and 50 million infections. The LHS-PRCC results indicated that in the context of vaccination rate, cumulative infections and deaths averted were most sensitive to vaccination rate, waning immunity rates from vaccination, and waning immunity from natural infection. This study's findings illustrate the impact of increasing vaccination coverage and/or reducing the transmission rate by NPI adherence in the prevention of COVID-19 infections and deaths in Ghana.

Exploring Social Media Network Connections to Assist During Public Health Emergency Response: A Retrospective Case-Study of Hurricane Matthew and Twitter Users in Georgia, USA.

OBJECTIVE: To assist communities who suffered from hurricane-inflicted damages, emergency responders may monitor social media messages. We present a case-study using the event of Hurricane Matthew to analyze the results of an imputation method for the location of Twitter users who follow school and school districts in Georgia, USA. METHODS: Tweets related to Hurricane Matthew were analyzed by content analysis with latent Dirichlet allocation models and sentiment analysis to identify needs and sentiment changes over time. A hurdle regression model was applied to study the association between retweet frequency and content analysis topics. RESULTS: Users residing in counties affected by Hurricane Matthew posted tweets related to preparedness (n = 171; 16%), awareness (n = 407; 38%), call-for-action or help (n = 206; 19%), and evacuations (n = 93; 9%), with mostly a negative sentiment during the preparedness and response phase. Tweets posted in the hurricane path during the preparedness and response phase were less likely to be retweeted than those outside the path (adjusted odds ratio: 0.95; 95% confidence interval: 0.75, 1.19). CONCLUSIONS: Social media data can be used to detect and evaluate damages of communities affected by natural disasters and identify users' needs in at-risk areas before the event takes place to aid during the preparedness phases.

Newcastle disease burden in Nepal and efficacy of Tablet I2 vaccine in commercial and backyard poultry production.

Poultry (Gallus domesticus) farming plays an important role as an income generating enterprise in a developing country like Nepal, contributing more than 4% to the national Gross Domestic Product (GDP). Newcastle Disease (ND) is a major poultry disease affecting both commercial and backyard poultry production worldwide. There were more than 90 reported ND outbreaks in Nepal in 2018 with over 74,986 birds being affected. ND is responsible for over 7% of total poultry mortality in the country. Recent outbreaks of ND in 2021 affected many farms throughout Nepal and caused massive loss in poultry production. ND is caused by a single-stranded ribonucleic acid (RNA) virus that presents very similar clinical symptoms as Influenza A (commonly known as bird flu) adding much complexity to clinical disease identification and intervention. We conducted a nationwide ND and Influenza A (IA) prevalence study, collecting samples from representative commercial and backyard poultry farms from across the major poultry production hubs of Nepal. We used both serological and molecular assessments to determine disease exposure history and identification of strains of ND Virus (NDV). Of the 40 commercial farms tested, both NDV (n = 28, 70%) and IAV (n = 11, 27.5%) antibodies were detected in majority of the samples. In the backyard farms (n = 36), sero-prevalence of NDV and IAV were 17.5% (n = 7) and 7.5% (n = 3) respectively. Genotype II NDV was present in most of the commercial farms, which was likely due to live vaccine usage. We detected never reported Genotype I NDV in two backyard farm samples. Our investigation into 2021 ND outbreak implicated Genotype VII.2 NDV strain as the causative pathogen. Additionally, we developed a Tablet formulation of the thermostable I2-NDV vaccine (Ranigoldunga™) and assessed its efficacy on various (mixed) breeds of chicken (Gallus domesticus). Ranigoldunga™ demonstrated an overall efficacy >85% with a stability of 30 days at room temperature (25°C). The intraocularly administered vaccine was highly effective in preventing ND, including Genotype VII.2 NDV strain.

Rapid genomic surveillance of SARS-CoV-2 in a dense urban community of Kathmandu Valley using sewage samples.

Understanding disease burden and transmission dynamics in resource-limited, low-income countries like Nepal are often challenging due to inadequate surveillance systems. These issues are exacerbated by limited access to diagnostic and research facilities throughout the country. Nepal has one of the highest COVID-19 case rates (915 cases per 100,000 people) in South Asia, with densely-populated Kathmandu experiencing the highest number of cases. Swiftly identifying case clusters (hotspots) and introducing effective intervention programs is crucial to mounting an effective containment strategy. The rapid identification of circulating SARS-CoV-2 variants can also provide important information on viral evolution and epidemiology. Genomic-based environmental surveillance can help in the early detection of outbreaks before clinical cases are recognized and identify viral micro-diversity that can be used for designing real-time risk-based interventions. This research aimed to develop a genomic-based environmental surveillance system by detecting and characterizing SARS-CoV-2 in sewage samples of Kathmandu using portable next-generation DNA sequencing devices. Out of 22 sites in the Kathmandu Valley from June to August 2020, sewage samples from 16 (80%) sites had detectable SARS-CoV-2. A heatmap was created to visualize the presence of SARS-CoV-2 infection in the community based on viral load intensity and corresponding geospatial data. Further, 47 mutations were observed in the SARS-CoV-2 genome. Some detected mutations (n = 9, 22%) were novel at the time of data analysis and yet to be reported in the global database, with one indicating a frameshift deletion in the spike gene. SNP analysis revealed possibility of assessing circulating major/minor variant diversity on environmental samples based on key mutations. Our study demonstrated the feasibility of rapidly obtaining vital information on community transmission and disease dynamics of SARS-CoV-2 using genomic-based environmental surveillance.

Climate change and health vulnerability in Nepal: A systematic review of the literature since 2010.

The Nepali population is among those most vulnerable to the health impacts of climate change. We conducted a systematic literature review to document the health effects of climate change in Nepal and identify knowledge gaps by examining vulnerability categories related to health. Three databases were searched for journal articles that addressed health and vulnerability related to climate change in Nepal from 2010 onwards. Of the 1063 articles identified, 37 were eligible for inclusion. The findings suggested the health of the population was affected mostly by food insecurity, floods, droughts, and reduced water levels. Studies revealed both morbidity and mortality increased due to climate change, with the most impacted populations being women, children, and the elderly. At greatest risk for impacts from climate change were those from poor and marginal populations, especially impoverished women. The public health sector, healthcare, and potable water sources were some of the least mentioned vulnerability subcategories, indicating more research is needed to better understand their adaptation capacities. We propose that identifying vulnerabilities and areas of limited research are critical steps in the prioritization of health policy and interventions for the most vulnerable populations in Nepal.

Transmission Dynamics of COVID-19 in Ghana and the Impact of Public Health Interventions.

This study characterized COVID-19 transmission in Ghana in 2020 and 2021 by estimating the time-varying reproduction number (Rt) and exploring its association with various public health interventions at the national and regional levels. Ghana experienced four pandemic waves, with epidemic peaks in July 2020 and January, August, and December 2021. The epidemic peak was the highest nationwide in December 2021 with Rt ≥ 2. Throughout 2020 and 2021, per-capita cumulative case count by region increased with population size. Mobility data suggested a negative correlation between Rt and staying home during the first 90 days of the pandemic. The relaxation of movement restrictions and religious gatherings was not associated with increased Rt in the regions with fewer case burdens. Rt decreased from > 1 when schools reopened in January 2021 to < 1 after vaccination rollout in March 2021. Findings indicated most public health interventions were associated with Rt reduction at the national and regional levels.

Firth's Logistic Regression of Interruption in Treatment before and after the Onset of COVID-19 among People Living with HIV on ART in Two Provinces of DRC.

The impact of the COVID-19 pandemic extends beyond the immediate physical effects of the virus, including service adjustments for people living with the human immunodeficiency virus (PLHIV) on antiretroviral therapy (ART). Purpose: To compare treatment interruptions in the year immediately pre-COVID-19 and after the onset of COVID-19 (10 April 2020 to 30 March 2021). Methods: We analyze quantitative data covering 36,585 persons with HIV who initiated antiretroviral treatment (ART) between 1 April 2019 and 30 March 2021 at 313 HIV/AIDS care clinics in the Haut-Katanga and Kinshasa provinces of the Democratic Republic of Congo (DRC), using Firth's logistic regression. Results: Treatment interruption occurs in 0.9% of clients and tuberculosis (TB) is detected in 1.1% of clients. The odds of treatment interruption are significantly higher (adjusted odds ratio: 12.5; 95% confidence interval, CI (8.5−18.3)) in the pre-COVID-19 period compared to during COVID-19. The odds of treatment interruption are also higher for clients with TB, those receiving ART at urban clinics, those younger than 15 years old, and female clients (p < 0.05). Conclusions: The clients receiving ART from HIV clinics in two provinces of DRC had a lower risk of treatment interruption during COVID-19 than the year before COVID-19, attributable to program adjustments.

Winter Storms and Unplanned School Closure Announcements on Twitter: Comparison Between the States of Massachusetts and Georgia, 2017-2018.

OBJECTIVE: This project aimed to quantify and compare Massachusetts and Georgia public school districts' 2017-2018 winter-storm-related Twitter unplanned school closure announcements (USCA). METHODS: Public school district Twitter handles and National Center for Education Statistics data were obtained for Georgia and Massachusetts. Tweets were retrieved using Twitter application programming interface. Descriptive statistics and regression analyses were conducted to compare the rates of winter-storm-related USCA. RESULTS: Massachusetts had more winter storms than Georgia during the 2017-2018 winter season, but Massachusetts school districts posted winter-storm-related USCA at a 60% lower rate per affected day (adjusted rate ratio, aRR = 0.40, 95% confidence intervals, CI: 0.30, 0.52) than Georgia school districts after controlling for the student enrollments and Twitter followers count per Twitter account. A 10-fold increase in followers count was correlated with a 118% increase in USCA rate per affected day (aRR = 2.18; 95% CI: 1.74, 2.75). Georgia school districts had a higher average USCA tweet rate per winter-storm-affected day than Massachusetts school districts. A higher number of Twitter followers was associated with a higher number of USCA tweets per winter-storm-affected day. CONCLUSION: Twitter accounts of school districts in Massachusetts had a lower tweet rate for USCA per winter-storm-affected days than those in Georgia.

Effective Practices and Recommendations for Drive-Through Clinic Points of Dispensing: A Systematic Review.

OBJECTIVE: Drive-through clinics (DTCs) are a novel type of point of dispensing where participants drive to a designated location and receive prophylaxis while remaining inside their vehicle. The objective of this review was to identify effective practices and recommendations for implementing DTCs for mass prophylaxis dispensing during emergency events. METHODS: A systematic review was conducted for articles covering DTCs published between 1990 and 2019. Inclusion criteria were peer-reviewed, written in English, and addressed DTCs sufficiently. Effective practices and recommendations identified in the literature were presented by theme. RESULTS: A total of 13 articles met inclusion criteria. The themes identified were (1) optimal DTC design and planning via decision support systems and decision support tools; (2) clinic layouts, locations, and design aspects; (3) staffing, training, and DTC communication; (4) throughput time; (5) community outreach methods; (6) DTC equipment; (7) infection prevention and personal protective equipment; and (8) adverse events prevention and traffic management. CONCLUSIONS: DTCs are an essential component of emergency preparedness and must be optimally designed and implemented to successfully dispense mass prophylaxis to a community within 48 hours. The effective practices and recommendations presented can be used for the development, implementation, and improvement of DTCs for their target populations.

Triggering of cardiovascular disease by infection type: The Atherosclerosis Risk in Communities study (ARIC).

INTRODUCTION: Acute infections are known triggers of cardiovascular disease (CVD) but how this association varies across infection types is unknown. We hypothesized while acute infections increase CVD risk, the strength of this association varies across infection types. METHOD: Acute coronary heart disease (CHD) and ischemic stroke cases were identified in the Atherosclerosis Risk in Communities Study (ARIC). ICD-9 codes from Medicare claims were used to identify cellulitis, pneumonia, urinary tract infections (UTI), and bloodstream infections. A case-crossover design and conditional logistic regression were used to compare infection types among acute CHD and stroke cases 14, 30, 42, and 90 days before the event with two corresponding control periods (1 and 2 years prior). RESULTS: Of the 1312 acute CHD cases, 116 had a UTI, 102 had pneumonia, 43 had cellulitis, and 28 had a bloodstream infection 90 days before the CHD event. Pneumonia (OR = 25.53 (9.21,70.78)), UTI (OR = 3.32 (1.93, 5.71)), bloodstream infections (OR = 5.93 (2.07, 17.00)), and cellulitis (OR = 2.58 (1.09, 6.13)) were associated with higher acute CHD risk within 14 days of infection. Of the 727 ischemic stroke cases, 12 had cellulitis, 27 had pneumonia, 56 had a UTI, and 5 had a bloodstream infection within 90 days of the stroke. Pneumonia (OR = 5.59 (1.77, 17.67)) and UTI (OR = 3.16 (1.68, 5.94)) were associated with higher stroke risk within 14 days of infection. CONCLUSIONS: Patients with pneumonia, UTI, or bloodstream infection appear to be at a 2.5 to 25.5 fold elevated CVD risk following infection. Preventive therapies during this high-risk period should be considered.

Health Reporting Characteristics among Journalists in Nepal Utilizing a One Health Framework.

Journalists play a crucial role in the dissemination of health-related information. In developing countries, such as Nepal, the media are integral in shaping the national agenda and informing the public of important health issues. With an increasing need for a collaborative effort to attain optimal health for people, animals, and the environment, the One Health approach was used to characterize health reporting in Nepal. A comprehensive survey was administered to health journalists regarding their public, animal, and environmental health reporting habits. Seventy-one journalists completed the survey across three study sites. Many journalists indicated a history of reporting across all three sectors but did not routinely focus on health reporting in general. The majority of journalists perceived the quality and overall coverage of health-related topics increased over the last five years. However, few journalists reported receiving specialized training in any health sector. Although the overall quality of health reporting in the Nepali media showed improvements, many journalists acknowledged a lack of understanding of common health topics and a desire to learn more skills related to accurate health reporting. One Health provides a conceptual framework for understanding and promoting health communication through mass media to benefit humans, animals, and ecosystems.

Spatially Refined Time-Varying Reproduction Numbers of COVID-19 by Health District in Georgia, USA, March-December 2020.

This study quantifies the transmission potential of SARS-CoV-2 across public health districts in Georgia, USA, and tests if per capita cumulative case count varies across counties. To estimate the time-varying reproduction number, Rt of SARS-CoV-2 in Georgia and its 18 public health districts, we apply the R package 'EpiEstim' to the time series of historical daily incidence of confirmed cases, 2 March-15 December 2020. The epidemic curve is shifted backward by nine days to account for the incubation period and delay to testing. Linear regression is performed between log10-transformed per capita cumulative case count and log10-transformed population size. We observe Rt fluctuations as state and countywide policies are implemented. Policy changes are associated with increases or decreases at different time points. Rt increases, following the reopening of schools for in-person instruction in August. Evidence suggests that counties with lower population size had a higher per capita cumulative case count on June 15 (slope = -0.10, p = 0.04) and October 15 (slope = -0.05, p = 0.03), but not on August 15 (slope = -0.04, p = 0.09), nor December 15 (slope = -0.02, p = 0.41). We found extensive community transmission of SARS-CoV-2 across all 18 health districts in Georgia with median 7-day-sliding window Rt estimates between 1 and 1.4 after March 2020.

Time-varying Reproduction Numbers of COVID-19 in Georgia, USA, March 2, 2020 to November 20, 2020.

BACKGROUND: In 2020, Severe Acute Respiratory Syndrome Coronavirus 2 impacted Georgia, USA. Georgia announced a state-wide shelter-in-place on April 2 and partially lifted restrictions on April 27. We estimated the time-varying reproduction numbers (Rt) of COVID-19 in Georgia, Metro Atlanta, and Dougherty County and environs from March 2, 2020, to November 20, 2020. METHODS: We analyzed the daily incidence of confirmed COVID-19 cases in Georgia, Metro Atlanta, and Dougherty County and its surrounding counties, and estimated Rt using the R package EpiEstim. We used a 9-day correction for the date of report to analyze the data by assumed date of infection. RESULTS: The median Rt estimate in Georgia dropped from between 2 and 4 in mid-March to < 2 in late March to around 1 from mid-April to November. Regarding Metro Atlanta, Rt fluctuated above 1.5 in March and around 1 since April. In Dougherty County, the median Rt declined from around 2 in late March to 0.32 on April 26. Then, Rt fluctuated around 1 in May through November. Counties surrounding Dougherty County registered an increase in Rt estimates days after a superspreading event occurred in the area. CONCLUSIONS: In Spring 2020, Severe Acute Respiratory Syndrome Coronavirus 2 transmission in Georgia declined likely because of social distancing measures. However, because restrictions were relaxed in late April and elections were conducted in November, community transmission continued, with Rt fluctuating around 1 across Georgia, Metro Atlanta, and Dougherty County as of November 2020. The superspreading event in Dougherty County affected surrounding areas, indicating the possibility of local transmission in neighboring counties.