Risk communication clarity and insurance demand: The case of the COVID-19 pandemic.

We study how the clarity of COVID-19 risk communications affects COVID-19 insurance demand using proprietary prefecture-level insurance data from China. We find that when local disclosures of COVID-19 risk contain case origin information, local purchases of COVID-19 insurance and local Internet searches for COVID-19 information increase, even after controlling for newly confirmed local cases and new deaths. Our results are robust to using the disclosure clarity of a major neighboring city. The findings suggest that providing improved knowledge about risk to individuals lead them to engage in more risk management. Our evidence contributes to the debate over how risk communication affects individuals' risk-related behaviors.

Surveillance and Response to Imported Malaria During the COVID-19 Epidemic - Anhui Province, China, 2019-2021.

What is already known about this topic?: China was certified malaria-free on June 30, 2021. However, imported malaria continuously threatens the effort to prevent re-establishment of malaria in China. What is added by this report?: Measures such as international travel restrictions, entry quarantine, and screening in fever clinics during the coronavirus disease 2019 (COVID-19) period were associated with a significant decrease of imported malaria cases in Anhui Province, a higher proportion of non-Plasmodium falciparum (non-P. falciparum) malaria reported infections, and a higher proportion of cases requiring medical attention at their initial visit. What are the implications for public health practices?: It is necessary to be vigilant about imported malaria during the COVID-19 epidemic, especially for non-P. falciparum infections which are more difficult to detect, and to promote research, development, and introduction of more sensitive and specific point-of-care detection methods for non-P. falciparum species.

Differential impact of non-pharmaceutical public health interventions on COVID-19 epidemics in the United States.

BACKGROUND: The widespread pandemic of novel coronavirus disease 2019 (COVID-19) poses an unprecedented global health crisis. In the United States (US), different state governments have adopted various combinations of non-pharmaceutical public health interventions (NPIs), such as non-essential business closures and gathering bans, to mitigate the epidemic from February to April, 2020. Quantitative assessment on the effectiveness of NPIs is greatly needed to assist in guiding individualized decision making for adjustment of interventions in the US and around the world. However, the impacts of these approaches remain uncertain. METHODS: Based on the reported cases, the effective reproduction number (Rt) of COVID-19 epidemic for 50 states in the US was estimated. Measurements on the effectiveness of nine different NPIs were conducted by assessing risk ratios (RRs) between Rt and NPIs through a generalized linear model (GLM). RESULTS: Different NPIs were found to have led to different levels of reduction in Rt. Stay-at-home contributed approximately 51% (95% CI 46-57%), wearing (face) masks 29% (15-42%), gathering ban (more than 10 people) 19% (14-24%), non-essential business closure 16% (10-21%), declaration of emergency 13% (8-17%), interstate travel restriction 11% (5-16%), school closure 10% (7-14%), initial business closure 10% (6-14%), and gathering ban (more than 50 people) 7% (2-11%). CONCLUSIONS: This retrospective assessment of NPIs on Rt has shown that NPIs played critical roles on epidemic control in the US in the past several months. The quantitative results could guide individualized decision making for future adjustment of NPIs in the US and other countries for COVID-19 and other similar infectious diseases.

Perceived uncertainty stress and its predictors among residents in China during the COVID-19 pandemic.

The prevalence of and risk factors for uncertainty stress among residents during the COVID-19 pandemic remain unclear. An online cross-sectional survey was conducted to explore and identify the risk factors for high perceived uncertainty stress among the general public in China during the COVID-19 outbreak. Information about the respondents' socioeconomic characteristics, knowledge of and attitudes towards COVID-19, perceived uncertainty stress, social capital, anxiety, and depressive symptoms was collected and analysed. Among the 1205 respondents, 45.3% (546) reported a high level of uncertainty stress. Multiple linear regression analysis indicated that anxiety (ß=3.871,P<0.001) and depression symptoms (ß=2.458, P<0.001), family residence (in towns or rural areas) (ß=0.947, P<0.001), lack of support for local epidemic control strategies (ß=1.253, P<0.001), worry about the pandemic (ß=1.191, P<0.001), and symptoms of weakness among family members (ß=1.525, P=0.002) were positively associated with perceived uncertainty stress. Cognitive social capital (ß=-0.883, P<0.001) and social networks (ß=-0.726, P<0.001) were negatively, but social participation (ß=0.714, P<0.001) was positively associated with perceived uncertainty stress. Our findings identify factors associated with a higher level of uncertainty stress and should be helpful in the consideration of effective policies and interventions for uncertainty stress during the initial phases of public health emergencies.