Public and health professional epidemic risk perceptions in countries that are highly vulnerable to epidemics: a systematic review

Background Risk communication interventions during epidemics aim to modify risk perceptions to achieve rapid shifts in population health behaviours. Exposure to frequent and often concurrent epidemics may influence how the public and health professionals perceive and respond to epidemic risks. This review aimed to systematically examine the evidence on risk perceptions of epidemic-prone diseases in countries highly vulnerable to epidemics. Methods We conducted a systematic review using PRISMA standards. We included peer-reviewed studies describing or measuring risk perceptions of epidemic-prone diseases among the general adult population or health professionals in 62 countries considered highly vulnerable to epidemics. We searched seven bibliographic databases and applied a four-stage screening and selection process, followed by quality appraisal. We conducted a narrative meta-synthesis and descriptive summary of the evidence, guided by the Social Amplification of Risk Framework. Results Fifty-six studies were eligible for the final review. They were conducted in eighteen countries and addressed thirteen epidemic-prone diseases. Forty-five studies were quantitative, six qualitative and five used mixed methods. Forty-one studies described epidemic risk perceptions in the general public and nineteen among health professionals. Perceived severity of epidemic-prone diseases appeared high across public and health professional populations. However, perceived likelihood of acquiring disease varied from low to moderate to high among the general public, and appeared consistently high amongst health professionals. Other occupational groups with high exposure to specific diseases, such as bushmeat handlers, reported even lower perceived likelihood than the general population. Among health professionals, the safety and effectiveness of the work environment and of the broader health system response influenced perceptions. Among the general population, disease severity, familiarity and controllability of diseases were influential factors. However, the evidence on how epidemic risk perceptions are formed or modified in these populations is limited. Conclusions The evidence affords some insights into patterns of epidemic risk perception and influencing factors, but inadequately explores what underlies perceptions and their variability, particularly among diseases, populations and over time. Approaches to defining and measuring epidemic risk perceptions are relatively underdeveloped. Graphical Abstract

Listening to Bluetooth Beacons for Epidemic Risk Mitigation

The ongoing COVID-19 pandemic let to efforts to develop and deploy digital contact tracing systems to expedite contact tracing and risk notification. Unfortunately, the success of these systems has been limited, partly owing to poor interoperability with manual contact tracing, low adoption rates, and a societally sensitive trade-off between utility and privacy. In this work, we introduce a new privacy-preserving and inclusive system for epidemic risk assessment and notification that aims to address these limitations. Rather than capturing pairwise encounters between user devices as done by existing systems, our system captures encounters between user devices and beacons placed in strategic locations where infection clusters may originate. Epidemiological simulations using an agent-based model demonstrate that, by utilizing location and environmental information and interoperating with manual contact tracing, our system can increase the accuracy of contact tracing actions and may help reduce epidemic spread already at low adoption.

The Occurrence of Heavy Air Pollution during the COVID-19 Outbreak in Beijing, China: Roles of Emission Reduction, Meteorological Conditions, and Regional Transport

To prevent the spread of coronavirus disease (COVID-19) and mitigate the epidemic risk, strict lockdown measures were implemented in Beijing during the quarantine period, significantly reducing human activities. However, severe air pollution episodes occurred frequently in Beijing. To explore the occurrence of severe air pollution during the quarantine period, the impacts of emission reductions, meteorological conditions, and regional transport on heavy air pollution were individually evaluated using the Community Multiscale Air Quality (CMAQ) model. Observations showed that the more unfavorable meteorological conditions which occurred during the pandemic as compared to the corresponding 2019 levels, including higher temperature, relative humidity, and frequency of strong southerly winds, and lower HPBL, led to an increase in PM2.5 concentrations. The model results also showed that the meteorological conditions in February 2020 favored PM2.5 formation. The PM2.5 concentrations were mainly dominated by regional transport, which became more significant in the quarantine period than in 2019, suggesting the importance of joint control on regional sources for reducing heavy air pollution. This study highlights that, although the emissions in Beijing and surrounding regions were largely reduced during the quarantine period, severe air pollution in Beijing did not reduce due to the unfavorable meteorological conditions.

Evaluating the Disaster Risk of the COVID-19 Pandemic Using an Ecological Niche Model

Since 2019, the novel coronavirus has spread rapidly worldwide, greatly affecting social stability and human health. Pandemic prevention has become China’s primary task in responding to the transmission of COVID-19. Risk mapping and the proposal and implementation of epidemic prevention measures emphasize many research efforts. In this study, we collected location information for confirmed COVID-19 cases in Beijing, Shenyang, Dalian, and Shijiazhuang from 5 October 2020 to 5 January 2021, and selected 15 environmental variables to construct a model that comprehensively considered the parameters affecting the outbreak and spread of COVID-19 epidemics. Annual average temperature, catering, medical facilities, and other variables were processed using ArcGIS 10.3 and classified into three groups, including natural environmental variables, positive socio-environmental variables, and benign socio-environmental variables. We modeled the epidemic risk distribution for each area using the MaxEnt model based on the case occurrence data and environmental variables in four regions, and evaluated the key environmental variables influencing the epidemic distribution. The results showed that medium-risk zones were mainly distributed in Changping and Shunyi in Beijing, while Huanggu District in Shenyang and the southern part of Jinzhou District and the eastern part of Ganjingzi District in Dalian also represented areas at moderate risk of epidemics. For Shijiazhuang, Xinle, Gaocheng and other places were key COVID-19 epidemic spread areas. The jackknife assessment results revealed that positive socio-environmental variables are the most important factors affecting the outbreak and spread of COVID-19. The average contribution rate of the seafood market was 21.12%, and this contribution reached as high as 61.3% in Shenyang. The comprehensive analysis showed that improved seafood market management, strengthened crowd control and information recording, industry-catered specifications, and well-trained employees have become urgently needed prevention strategies in different regions. The comprehensive analysis indicated that the niche model could be used to classify the epidemic risk and propose prevention and control strategies when combined with the assessment results of the jackknife test, thus providing a theoretical basis and information support for suppressing the spread of COVID-19 epidemics.

The Epidemic Risk of Dengue Fever in Japan: Climate Change and Seasonality

Dengue fever is a leading cause of illness and death in the tropics and subtropics, and the disease has become a threat to many nonendemic countries where the competent vectors such as Aedes albopictus and Aedes aegypti are abundant. The dengue epidemic in Tokyo, 2014, poses the critical importance to accurately model and predict the outbreak risk of dengue fever in nonendemic regions. Using climatological datasets and traveler volumes in Japan, where dengue was not seen for 70 years by 2014, we investigated the outbreak risk of dengue in 47 prefectures, employing the temperature-dependent basic reproduction number and a branching process model. Our results show that the effective reproduction number varies largely by season and by prefecture, and, moreover, the probability of outbreak if an untraced case is imported varies greatly with the calendar time of importation and location of destination. Combining the seasonally varying outbreak risk with time-dependent traveler volume data, the unconditional outbreak risk was calculated, illustrating different outbreak risks between southern coastal areas and northern tourist cities. As the main finding, the large travel volume with nonnegligible risk of outbreak explains the reason why a summer outbreak in Tokyo, 2014, was observed. Prefectures at high risk of future outbreak would be Tokyo again, Kanagawa or Osaka, and highly populated prefectures with large number of travelers.

Assessing countermeasures during a hepatitis A virus outbreak among men who have sex with men

Background A hepatitis A epidemic occurred among men who have sex with men (MSM) in Japan in 2017–2018. In this study, we employ a parsimonious mathematical model to epidemiologically investigate the dynamics of infection, aiming to evaluate the effectiveness of campaign-based interventions among MSM to raise awareness of the situation. Methods A mathematical model describing a mixture of human-to-human transmission and environmental transmission was fitted to surveillance data. Taking seasonally varying environmental transmission into account, we estimated the reproduction number of hepatitis A virus during the course of epidemic, and, especially, the abrupt decline in this reproduction number following campaign-based interventions. Results The reproduction number prior to the countermeasures ranged from 2.6 to 3.1 and then began to decrease following campaign-based interventions. After the first countermeasure, the reproduction number decreased, but the epidemic remained supercritical (i.e., Rt > 1). The value of Rt dropped well below one following the second countermeasure, which used web articles to widely disseminate information about the epidemic risk. Conclusions Although the effective reproduction number, Rt, changes because of both intrinsic and extrinsic factors, the timing of the examined countermeasures against hepatitis A in the MSM population was consistent with the abrupt declines observed in Rt. Even without vaccination, the epidemic was brought under control, and risky behaviors may have been changed by the increase in situation awareness reached through web articles.

Customized treatment protocols for patients with closed fracture in hospitals at varying coronavirus disease 2019 (COVID-19) risk

Background To determine an optimized treatment protocol during the COVID-19 epidemic for patients with closed fracture and delayed surgery. Methods The epidemic data of three hospitals, randomly selected from different administrative regions of Wuhan, were analyzed retrospectively from 23 January to 31 March 2020. Changes in the number of confirmed cases per day (cumulative and new) of each region were tracked as a reflection of changing epidemic risk levels. The risk level map was drawn. The epidemic status, treatment protocols, and treatment efficiencies for patients with closed fracture in the three hospitals were compared. Results Overall, 138 patients with closed fracture were admitted. Each hospital had established its own protocol, according to the initial perceived risk. Based on the risk level map, over the study period, the risk levels of the three regions changed independently and were not in sync. All patients recovered and were timely discharged. No staff member was detected with COVID-19. Conclusions The COVID-19 risk level of each area is dynamic. To optimize medical resources, avoid cross-infection, and improve efficiency, changes in epidemic risk should be monitored. For patients with closed fracture, treatment protocols should be adjusted according to changes in epidemic risk.

Projecting the COVID-19 epidemic risk in France for the summer 2021

The next weeks will be critical in determining the conditions and timing of the 4th wave of COVID-19 in France. We assessed epidemic risk to assist spatially targeted surveillance and control. Southwest is estimated to be at highest risk, due to summer crowding, low acquired immunity, and Delta variant hotspots.