Lagged meteorological impacts on COVID-19 incidence among high-risk counties in the United States-a spatiotemporal analysis.

BACKGROUND: The associations between meteorological factors and coronavirus disease 2019 (COVID-19) have been discussed globally; however, because of short study periods, the lack of considering lagged effects, and different study areas, results from the literature were diverse and even contradictory. OBJECTIVE: The primary purpose of this study is to conduct more reliable research to evaluate the lagged meteorological impacts on COVID-19 incidence by considering a relatively long study period and diversified high-risk areas in the United States. METHODS: This study adopted the distributed lagged nonlinear model with a spatial function to analyze COVID-19 incidence predicted by multiple meteorological measures from March to October of 2020 across 203 high-risk counties in the United States. The estimated spatial function was further smoothed within the entire continental United States by the biharmonic spline interpolation. RESULTS: Our findings suggest that the maximum temperature, minimum relative humidity, and precipitation were the best meteorological predictors. Most significantly positive associations were found from 3 to 11 lagged days in lower levels of each selected meteorological factor. In particular, a significantly positive association appeared in minimum relative humidity higher than 88.36% at 5-day lag. The spatial analysis also shows excessive risks in the north-central United States. SIGNIFICANCE: The research findings can contribute to the implementation of early warning surveillance of COVID-19 by using weather forecasting for up to two weeks in high-risk counties.

Assessing Determinants of COVID-19 Vaccine Hesitancy in Nevada.

In December 2020, we conducted a telephone survey to determine what factors are connected to COVID-19 vaccine hesitancy among adults in Nevada. The survey was based on factors identified in other studies, such as demographic variables (age, race, ethnicity, gender, household income, urbanicity, educational attainment), health status, previous COVID-19 infections, social media engagement, adherence to social distancing guidelines, beliefs about COVID-19, and political ideology identifications. Using a proportional odds model, we compared vaccine hesitancy levels to determine the odds of being more likely versus unlikely to get the COVID-19 vaccine. Of 1,000 people surveyed, 30.4% exhibited vaccine hesitancy. Findings showed that adults with significantly lower odds of vaccine hesitancy included those who were male, older, worried about COVID-19 infection or its community effects, adhered to social distancing, and reported higher incomes. Adults who identified as African American or Black or as multiple or "other" races exhibited significantly higher odds of vaccine hesitancy than White adults. Adults self-identifying as conservative had significantly higher odds of vaccine hesitancy than others. Vaccine hesitancy levels suggest possible hurdles to addressing the COVID-19 pandemic in a state with high visitor volumes and demographics that resemble the country's future as minority White, highlighting possible lessons for future pandemics. Most measures of COVID-19 worry were not significantly associated with vaccine hesitancy, suggesting that vaccination efforts should focus on other motivators. COVID-19 vaccination efforts should also directly encourage uptake by younger and middle-aged adults who are female, African American, have lower incomes, and identify as conservative.

Meteorological impacts on the incidence of COVID-19 in the U.S.

Since the World Health Organization has declared the current outbreak of the novel coronavirus (COVID-19) a global pandemic, some have been anticipating that the mitigation could happen in the summer like seasonal influenza, while medical solutions are still in a slow progress. Experimental studies have revealed a few evidences that coronavirus decayed quickly under the exposure of heat and humidity. This study aims to carry out an epidemiological investigation to establish the association between meteorological factors and COVID-19 in high risk areas of the United States (U.S.). We analyzed daily new confirmed cases of COVID-19 and seven meteorological measures in top 50 U.S. counties with the most accumulative confirmed cases from March 22, 2020 to April 22, 2020. Our analyses indicate that each meteorological factor and COVID-19 more likely have a nonlinear association rather than a linear association over the wide ranges of temperature, relative humidity, and precipitation observed. Average temperature, minimum relative humidity, and precipitation were better predictors to address the meteorological impact on COVID-19. By including all the three meteorological factors in the same model with their lagged effects up to 3 days, the overall impact of the average temperature on COVID-19 was found to peak at 68.45 °F and decrease at higher degrees, though the overall relative risk percentage (RR %) reduction did not become significantly negative up to 85 °F. There was a generally downward trend of RR % with the increase of minimum relative humidity; nonetheless, the trend reversed when the minimum relative humidity exceeded 91.42%. The overall RR % of COVID-19 climbed to the highest level of 232.07% (95% confidence interval = 199.77, 267.85) with 1.60 inches of precipitation, and then started to decrease. When precipitation exceeded 1.85 inches, its impact on COVID-19 became significantly negative. Our findings alert people to better have self-protection during the pandemic rather than expecting that the natural environment can curb coronavirus for human beings.

COVID-19 Outbreak, Mitigation, and Governance in High Prevalent Countries.

Background: Disease control involves multiple actions overtime to halt the spread of COVID-19. The role of a country's governance in slowing the spread of COVID-19 has not yet been well investigated. Objective: This study aims to investigate the association between governance and the trend of COVID-19 incidence in countries with the highest prevalence. We hypothesized that countries with better governance are more likely to mitigate the spread of COVID-19 than countries with worse governance. Methods: We analyzed 62 most prevalent countries with at least 10,000 accumulative confirmed cases from January 22 to June 15, 2020. Countries were further grouped into three different levels of governance (25 better governance, 24 fair governance, and 13 worse governance), identified outbreak and mitigation periods using the joinpoint regression model, and compared the number of days and average daily percent change in incidence in two periods by governance level using the one-way analysis of variance. Findings: The average outbreak period in the 62 countries lasted 84.0 days. Sixty percent of countries (N = 37) had experienced outbreak periods, followed by a mitigation period. In contrast, the rest forty percent of countries (N = 25) still had a rising trend. In the outbreak period, better governance countries had a more rapid increase but a shorter outbreak period (71.2 days) than countries with fair (93.5 days) and worse (90.8 days) governance. Most countries with better governance (84.0%) revealed a declining trend in COVID-19 incidence, while such a trend was less than half of fair and worse governance countries (38.5%-41.7%). Conclusions: Countries with better governance are more resilient during the COVID-19 crisis. While the mitigation of COVID-19 is observed in most better governance countries, the incidence of COVID-19 is still surging in most fair and worse governance countries, and the possibility of a recurring epidemic of COVID-19 in countries cannot be ignored.

Nonuniform impacts of COVID-19 lockdown on air quality over the United States.

Most of the state governments in United States (U.S.) issued lockdown or business restrictions amid the COVID-19 pandemic in March 2020, which created a unique opportunity to evaluate the air quality response to reduced economic activities. Data acquired from 28 long-term air quality stations across the U.S. revealed widespread but nonuniform reductions of nitrogen dioxide (NO2) and carbon monoxide (CO) during the first phase of lockdown (March 15-April 25, 2020) relative to a pre-lockdown reference period and historical baselines established in 2017-2019. The reductions, up to 49% for NO2 and 37% for CO, are statistically significant at two thirds of the sites and tend to increase with local population density. Significant reductions of particulate matter (PM2.5 and PM10) only occurred in the Northeast and California/Nevada metropolises where NO2 declined the most, while the changes in ozone (O3) were mixed and relatively minor. These findings are consistent with lower transportation and utility demands that dominate NO2 and CO emissions, especially in major urban areas, due to the lockdown. This study provides an insight into potential public health benefits with more aggressive air quality management, which should be factored into strategies to reopen the U.S. and global economy.