Nonpharmaceutical Interventions in Georgia: Public Health Implications.

OBJECTIVES: As coronavirus disease 2019 (COVID-19) spread, many states implemented nonpharmaceutical interventions in the absence of effective therapies with varying degrees of success. Our aim was to evaluate restrictions comparing two regions of Georgia and their impact on outcomes as measured by confirmed illness and deaths. METHODS: Using The New York Times COVID-19 incidence data and mandate information from various web sites, we examined trends in cases and deaths using joinpoint analysis at the region and county level before and after the implementation of a mandate. RESULTS: We found that rates of cases and deaths showed the greatest decrease in acceleration after the simultaneous implementation of a statewide shelter-in-place for vulnerable populations combined with social distancing for businesses and limiting gatherings to <10 people. County-level shelters-in-place, business closures, limits on gatherings to <10, and mask mandates showed significant case rate decreases after a county implemented them. School closures had no consistent effect on either outcome. CONCLUSIONS: Our findings indicate that protecting vulnerable populations, implementing social distancing, and mandating masks may be effective countermeasures to containment while mitigating the economic and psychosocial effects of strict shelters-in-place and business closures. In addition, states should consider allowing local municipalities the flexibility to enact nonpharmaceutical interventions that are more or less restrictive than the state-level mandates under some conditions in which the data indicate it is necessary to protect communities from disease or undue economic burden.

The Relationship between Health Literacy and COVID-19 Vaccination Prevalence during a Rapidly Evolving Pandemic and Infodemic.

The gap between how health information is communicated and what people understand and can use to make informed health decisions is called health literacy. This gap was exacerbated by the rapidly changing and excessive volume of information, misinformation, and disinformation during the COVID-19 pandemic. People with lower health literacy may not have understood the importance of COVID-19 vaccination for themselves or for their communities. Our aim was to understand health literacy levels within Fulton County, Georgia, and their relationship to vaccine prevalence. Fulton county residents ages 18 and over (n = 425) completed an on-line Health Literacy Questionnaire. Individual, organizational, functional, interactive, and critical health literacy scales were created. Vaccination prevalence data were collected from the Georgia Vaccine Distribution Dashboard. All data were divided into one of three county areas. There were statistically significant variations in vaccine prevalence χ2(3) = 29.325, p < 0.001 among the three county areas. All levels of health literacy predicted overall county vaccination prevalence F (4,420) = 85.941, p < 0.001, There were significant differences in health literacy levels among two of the three county area pairs; the lowest resourced county area had the lowest vaccination prevalence and health literacy rates. This is the first example of relating direct health literacy measures across a major metropolitan US county with vaccine prevalence data.

Strengthening Culturally Competent Health Communication.

Vulnerable refugee communities are disproportionately affected by the ongoing COVID-19 pandemic; existing longstanding health inequity in these communities is exacerbated by ineffective risk communication practices about COVID-19. Culturally and linguistically appropriate health communication following health literacy guidelines is needed to dispel cultural myths, social stigma, misinformation, and disinformation. For refugee communities, the physical, mental, and social-related consequences of displacement further complicate understanding of risk communication practices grounded in a Western cultural ethos. We present a case study of Clarkston, Georgia, the "most diverse square mile in America," where half the population is foreign born and majority refugee. Supporting marginalized communities in times of risk will require a multipronged, systemic approach to health communication including: (1) creating a task force of local leaders and community members to deal with emergent issues; (2) expanding English-language education and support for refugees; (3) including refugee perspectives on risk, health, and wellness into risk communication messaging; (4) improving cultural competence and health literacy training for community leaders and healthcare providers; and (5) supporting community health workers. Finally, better prepared public health programs, including partnerships with trusted community organizations and leadership, can ensure that appropriate and supportive risk communication and health education and promotion are in place long before the next emergency.

Transmission dynamics and control of COVID-19 in Chile, March-October, 2020.

Since the detection of the first case of COVID-19 in Chile on March 3rd, 2020, a total of 513,188 cases, including ~14,302 deaths have been reported in Chile as of November 2nd, 2020. Here, we estimate the reproduction number throughout the epidemic in Chile and study the effectiveness of control interventions especially the effectiveness of lockdowns by conducting short-term forecasts based on the early transmission dynamics of COVID-19. Chile's incidence curve displays early sub-exponential growth dynamics with the deceleration of growth parameter, p, estimated at 0.8 (95% CI: 0.7, 0.8) and the reproduction number, R, estimated at 1.8 (95% CI: 1.6, 1.9). Our findings indicate that the control measures at the start of the epidemic significantly slowed down the spread of the virus. However, the relaxation of restrictions and spread of the virus in low-income neighborhoods in May led to a new surge of infections, followed by the reimposition of lockdowns in Greater Santiago and other municipalities. These measures have decelerated the virus spread with R estimated at ~0.96 (95% CI: 0.95, 0.98) as of November 2nd, 2020. The early sub-exponential growth trend (p ~0.8) of the COVID-19 epidemic transformed into a linear growth trend (p ~0.5) as of July 7th, 2020, after the reimposition of lockdowns. While the broad scale social distancing interventions have slowed the virus spread, the number of new COVID-19 cases continue to accrue, underscoring the need for persistent social distancing and active case detection and isolation efforts to maintain the epidemic under control.

Early transmission dynamics of COVID-19 in a southern hemisphere setting: Lima-Peru: February 29th-March 30th, 2020.

The COVID-19 pandemic that emerged in Wuhan China has generated substantial morbidity and mortality impact around the world during the last four months. The daily trend in reported cases has been rapidly rising in Latin America since March 2020 with the great majority of the cases reported in Brazil followed by Peru as of April 15th, 2020. Although Peru implemented a range of social distancing measures soon after the confirmation of its first case on March 6th, 2020, the daily number of new COVID-19 cases continues to accumulate in this country. We assessed the early COVID-19 transmission dynamics and the effect of social distancing interventions in Lima, Peru. We estimated the reproduction number, R, during the early transmission phase in Lima from the daily series of imported and autochthonous cases by the date of symptoms onset as of March 30th, 2020. We also assessed the effect of social distancing interventions in Lima by generating short-term forecasts grounded on the early transmission dynamics before interventions were put in place. Prior to the implementation of the social distancing measures in Lima, the local incidence curve by the date of symptoms onset displays near exponential growth dynamics with the mean scaling of growth parameter, p, estimated at 0.96 (95% CI: 0.87, 1.0) and the reproduction number at 2.3 (95% CI: 2.0, 2.5). Our analysis indicates that school closures and other social distancing interventions have helped slow down the spread of the novel coronavirus, with the nearly exponential growth trend shifting to an approximately linear growth trend soon after the broad scale social distancing interventions were put in place by the government. While the interventions appear to have slowed the transmission rate in Lima, the number of new COVID-19 cases continue to accumulate, highlighting the need to strengthen social distancing and active case finding efforts to mitigate disease transmission in the region.

Protocol for a national probability survey using home specimen collection methods to assess prevalence and incidence of SARS-CoV-2 infection and antibody response.

PURPOSE: The U.S. response to the SARS-CoV-2 epidemic has been hampered by early and ongoing delays in testing for infection; without data on where infections were occurring and the magnitude of the epidemic, early public health responses were not data-driven. Understanding the prevalence of SARS-CoV-2 infections and immune response is critical to developing and implementing effective public health responses. Most serological surveys have been limited to localities that opted to conduct them and/or were based on convenience samples. Moreover, results of antibody testing might be subject to high false positive rates in the setting of low prevalence of immune response and imperfect test specificity. METHODS: We will conduct a national serosurvey for SARS-CoV-2 PCR positivity and immune experience. A probability sample of U.S. addresses will be mailed invitations and kits for the self-collection of anterior nares swab and finger prick dried blood spot specimens. Within each sampled household, one adult 18 years or older will be randomly selected and asked to complete a questionnaire and to collect and return biological specimens to a central laboratory. Nasal swab specimens will be tested for SARS-CoV-2 RNA by RNA PCR; dried blood spot specimens will be tested for antibodies to SARS-CoV-2 (i.e., immune experience) by enzyme-linked immunoassays. Positive screening tests for antibodies will be confirmed by a second antibody test with different antigenic basis to improve predictive value of positive (PPV) antibody test results. All persons returning specimens in the baseline phase will be enrolled into a follow-up cohort and mailed additional specimen collection kits 3 months after baseline. A subset of 10% of selected households will be invited to participate in full household testing, with tests offered for all household members aged ≥3 years. The main study outcomes will be period prevalence of infection with SARS-CoV-2 and immune experience, and incidence of SARS-CoV-2 infection and antibody responses. RESULTS: Power calculations indicate that a national sample of 4000 households will facilitate estimation of national SARS-CoV-2 infection and antibody prevalence with acceptably narrow 95% confidence intervals across several possible scenarios of prevalence levels. Oversampling in up to seven populous states will allow for prevalence estimation among subpopulations. Our 2-stage algorithm for antibody testing produces acceptable PPV at prevalence levels ≥1.0%. Including oversamples in states, we expect to receive data from as many as 9156 participants in 7495 U.S. households. CONCLUSIONS: In addition to providing robust estimates of prevalence of SARS-CoV-2 infection and immune experience, we anticipate this study will establish a replicable methodology for home-based SARS-CoV-2 testing surveys, address concerns about selection bias, and improve positive predictive value of serology results. Prevalence estimates of SARS-CoV-2 infection and immune experience produced by this study will greatly improve our understanding of the spectrum of COVID-19 disease, its current penetration in various demographic, geographic, and occupational groups, and inform the range of symptoms associated with infection. These data will inform resource needs for control of the ongoing epidemic and facilitate data-driven decisions for epidemic mitigation strategies.

Short-term Forecasts of the COVID-19 Epidemic in Guangdong and Zhejiang, China: February 13-23, 2020.

The ongoing COVID-19 epidemic continues to spread within and outside of China, despite several social distancing measures implemented by the Chinese government. Limited epidemiological data are available, and recent changes in case definition and reporting further complicate our understanding of the impact of the epidemic, particularly in the epidemic's epicenter. Here we use previously validated phenomenological models to generate short-term forecasts of cumulative reported cases in Guangdong and Zhejiang, China. Using daily reported cumulative case data up until 13 February 2020 from the National Health Commission of China, we report 5- and 10-day ahead forecasts of cumulative case reports. Specifically, we generate forecasts using a generalized logistic growth model, the Richards growth model, and a sub-epidemic wave model, which have each been previously used to forecast outbreaks due to different infectious diseases. Forecasts from each of the models suggest the outbreaks may be nearing extinction in both Guangdong and Zhejiang; however, the sub-epidemic model predictions also include the potential for further sustained transmission, particularly in Zhejiang. Our 10-day forecasts across the three models predict an additional 65-81 cases (upper bounds: 169-507) in Guangdong and an additional 44-354 (upper bounds: 141-875) cases in Zhejiang by February 23, 2020. In the best-case scenario, current data suggest that transmission in both provinces is slowing down.