Comparing the gestational diabetes mellitus prevalence and oral glucose tolerance test characteristics before and after the COVID-19 outbreak in Hongshan District of Wuhan, China, 2018- 2021 (preprint)

Background: The Coronavirus Disease 2019 (COVID-19) pandemic has significantly impacted the management and prevalence of gestational diabetes mellitus (GDM) among pregnant women worldwide. This study aimed to investigate the effects of the pandemic on GDM prevalence and oral glucose tolerance test (OGTT) characteristics in Hongshan District, Wuhan, China. Methods: We retrospectively analyzed data from 91,932 pregnant women screened for GDM before (January 1, 2018, to December 31, 2019) and after (January 1, 2020, to December 31, 2021) the onset of the COVID-19 pandemic. The study focused on changes in GDM prevalence, OGTT positive rates and glucose value distribution, and the diagnostic performance of OGTT. Results: The prevalence of GDM increased significantly from 14.5% (95% CI, 14.2-14.8%) pre-pandemic to 21.9% (95% CI, 21.5-22.4%) post-pandemic. A notable rise in OGTT positive rates was observed across all time points, with the most significant increase at the 0-hour mark. Regression analysis indicated a significant risk increase for GDM during the pandemic, even after adjusting for age. Diagnostic accuracy of the 0-hour OGTT improved in the pandemic era, with the area under the curve (AUC) rising from 0.78 to 0.79 and sensitivity from 0.56 to 0.58. Median OGTT values at all time points significantly increased post-pandemic, even after adjusting for age, indicating a shift in glucose metabolism among the study population. Conclusion: The COVID-19 pandemic has led to a significant increase in the prevalence of GDM among pregnant women in Hongshan District, Wuhan. This is evidenced by the elevated rates of positive OGTT and altered median glucose values, indicating a shift in glucose metabolism. These findings underscore the profound impact of the pandemic on maternal and neonatal health. They emphasize the imperative for continuous monitoring and the development of updated, localized diagnostic criteria for OGTT to enhance the identification and treatment of GDM during and after global health crises.

Effectiveness of non-pharmaceutical interventions on COVID-19 transmission in 190 countries from 23 January to 13 April 2020.

BACKGROUND: To evaluate and compare the effectiveness of four types of non-pharmaceutical interventions (NPIs) to contain the time-varying effective reproduction number (Rt) of coronavirus disease-2019 (COVID-19). METHODS: This study included 1,908,197 confirmed COVID-19 cases from 190 countries between 23 January and 13 April 2020. The implemented NPIs were categorised into four types: mandatory face mask in public, isolation or quarantine, social distancing and traffic restriction (referred to as mandatory mask, quarantine, distancing and traffic hereafter, respectively). RESULTS: The implementations of mandatory mask, quarantine, distancing and traffic were associated with changes (95% confidence interval, CI) of -15.14% (from -21.79% to -7.93%), -11.40% (from -13.66% to -9.07%), -42.94% (from -44.24% to -41.60%) and -9.26% (from -11.46% to -7.01%) in the Rt of COVID-19 when compared with those without the implementation of the corresponding measures. Distancing and the simultaneous implementation of two or more types of NPIs seemed to be associated with a greater decrease in the Rt of COVID-19. CONCLUSION: Our study indicates that NPIs can significantly contain the COVID-19 pandemic. Distancing and the simultaneous implementation of two or more NPIs should be the strategic priorities for containing COVID-19.

Meteorological factors and COVID-19 incidence in 190 countries: An observational study.

Novel corona virus disease 2019 (COVID-19), which first emerged in December 2019, has become a pandemic. This study aimed to investigate the associations between meteorological factors and COVID-19 incidence and mortality worldwide. This study included 1,908,197 confirmed cases of and 119,257 deaths from COVID-19 from 190 countries between 23 January and 13 April, 2020. We used a distributed lag non-linear model with city-/country-level random intercept to investigate the associations between COVID19 incidence and daily temperature, relative humidity, and wind speed. A series of confounders were considered in the analysis including demographics, socioeconomics, geographic locations, and political strategies. Sensitivity analyses were performed to examine the robustness of the associations. The COVID-19 incidence showed a stronger association with temperature than with relative humidity or wind speed. An inverse association was identified between the COVID-19 incidence and temperature. The corresponding 14-day cumulative relative risk was 1.28 [95% confidence interval (CI), 1.20-1.36] at 5 °C, and 0.75 (95% CI, 0.65-0.86) at 22 °C with reference to the risk at 11 °C. An inverse J-shaped association was observed between relative humidity and the COVID-19 incidence, with the highest risk at 72%. A higher wind speed was associated with a generally lower incidence of COVID-19, although the associations were weak. Sensitivity analyses generally yielded similar results. The COVID-19 incidence decreased with the increase of temperature. Our study suggests that the spread of COVID-19 may slow during summer but may increase during winter.