Variation in Cause-Specific Mortality Rates in Italy during the First Wave of the COVID-19 Pandemic: A Study Based on Nationwide Data

Italy was a country severely hit by the first coronavirus disease 2019 (COVID-19) pandemic wave in early 2020. Mortality studies have focused on the overall excess mortality observed during the pandemic. This paper investigates the cause-specific mortality in Italy from March 2020 to April 2020 and the variation in mortality rates compared with those in 2015–2019 regarding sex, age, and epidemic area. Causes of death were derived from the national cause-of-death register. COVID-19 was the leading cause of death among males and the second leading cause among females. Chronic diseases, such as diabetes and hypertensive, ischemic heart, and cerebrovascular diseases, with decreasing or stable mortality rates in 2015–2019, showed a reversal in the mortality trend. Moreover, mortality due to pneumonia and influenza increased. No increase in neoplasm mortality was observed. Among external causes of death, mortality increased for accidental falls but reduced for transport accidents and suicide. Mortality from causes other than COVID-19 increased similarly in both genders and more at ages 65 years or above. Compared with other areas in Italy, the Lombardy region showed the largest excess in mortality for all leading causes. Underdiagnosis of COVID-19 at the beginning of the pandemic may, to some extent, explain the mortality increase for some causes of death, especially pneumonia and other respiratory diseases.

The feasibility of field collected pig oronasal secretions as specimens for the virologic surveillance of Japanese encephalitis virus

Virologic surveillance of Japanese encephalitis virus (JEV) relies on collecting pig blood specimens and adult mosquitoes in the past. Viral RNAs extracted from pig blood specimens suffer from low detecting positivity by reverse transcription PCR (RT-PCR). The oronasal transmission of the virus has been demonstrated in experimentally infected pigs. This observation suggested oronasal specimens could be useful source in the virus surveillance. However, the role of this unusual route of transmission remains unproven in the operational pig farm. In this study, we explore the feasibility of using pig oronasal secretions collected by chewing ropes to improve the positivity of detection in commercial pig farms. The multiplex genotype-specific RT-PCR was used in this study to determine and compare the positivity of detecting JEV viral RNAs in pig’s oronasal secretions and blood specimens, and the primary mosquito vector. Oronasal specimens had the overall positive rate of 6.0% (95% CI 1.3%–16.6%) (3/50) to 10.0% (95% CI 2.1%–26.5%) (3/30) for JEV during transmission period despite the negative results of all blood-derived specimens (n = 2442). Interestingly, pig oronasal secretions and female Culex tritaeniorhynchus mosquito samples collected from the same pig farm showed similar viral RNA positive rates, 10.0% (95% CI 2.1%–26.5%) (3/30) and 8.9% (95% CI 2.5%–21.2%) (4/45), respectively (p> 0.05). Pig oronasal secretion-based surveillance revealed the seasonality of viral activity and identified closely related genotype I virus derived from the mosquito isolates. This finding indicates oronasal secretion-based RT-PCR assay can be a non-invasive, alternative method of implementing JEV surveillance in the epidemic area prior to the circulation of virus-positive mosquitoes.

Impact of Epidemic-Affected Labor Shortage on Food Safety: A Chinese Scenario Analysis Using the CGE Model

Human food safety should be given priority during a major public health crisis. As the primary element of agricultural production, labor tends to suffer the most during a period of public health concern. Studying the impact of epidemic-affected labor shortages on agricultural production, trade, and prices has important implications for food security. This study used a calculable general equilibrium model to study the changes in China’s agricultural production, trade, and prices under different labor damage scenarios. The results showed that agricultural production was less affected under a scenario where the epidemic was controlled locally. The output of agricultural products decreased by about 2.19%, and the prices of agricultural products increased slightly. However, the nationwide output of agricultural products decreased by only 0.1%, and the prices remained largely stable. In the case of the spread of the epidemic, the output of agricultural products in the epidemic area decreased by 2.11%, and the prices of certain agricultural products increased significantly. For example, the price of vegetables increased by 0.78%, the price of pork increased by about 0.7%, and those of agricultural products in other parts of the country also increased slightly. Compared with the national spread scenario, the local outbreak scenario had a smaller impact on China’s food security, indicating China’s effective policy against the epidemic. Although the impact of labor shortage under the influence of the epidemic on China was relatively limited, and considering its stable food security, we should pay attention to the increase in the process of agricultural products and changes in agricultural trade in the epidemic area. The residents in the epidemic areas could not effectively obtain nutritious food, which affected their health. Thus, the government should also completely mobilize agricultural resources to ensure the nutrition safety of residents during major public health incidents.

The Effect of Governmental Health Measures on Public Behaviour During the COVID-19 Pandemic Outbreak

Background: The COVID-19 pandemic resulted in radical changes in many aspects of life. To deal with this, each country has implemented continuous health measures from the beginning of the outbreak. Discovering how governmental actions impacted public behaviour during the outbreak stage is the purpose of this study. Methods: This study uses a hybrid large-scale data visualisation method to analyse public behaviour (epidemic concerns, self-protection, and mobility trends), using the data provided by multiple authorities. Meanwhile, a content analysis method is used to qualitatively code the health measures of three countries with severe early epidemic outbreaks from different continents, namely China, Italy, and the United States. Eight dimensions are coded to rate the mobility restrictions implemented in the above countries. Results: (1) Governmental measures did not immediately persuade the public to change their behaviours during the COVID-19 epidemic. Instead, the public behaviour proceeded in a three-phase rule, which is typically witnessed in an epidemic outbreak, namely the wait-and-see phase, the surge phase and the slow-release phase. (2) The strictness of the mobility restrictions of the three countries can be ranked as follows: Hubei Province in China (with an average score of 8.5 out of 10), Lombardy in Italy (7.125), and New York State in the United States (5.375). Strict mobility restrictions are more likely to cause a surge of population outflow from the epidemic area in the short term, whereas the effect of mobility restrictions is positively related to the stringency of policies in the long term. Conclusion: The public showed generally lawful behaviour during regional epidemic outbreaks and blockades. Meanwhile public behaviour was deeply affected by the actions of local governments, rather than the global pandemic situation. The contextual differences between the various countries are important factors that influence the effects of the different governments’ health measures.

On the Transmission of COVID-19 and Its Prevention and Control Management

The spread of an epidemic is a typical public emergency and also one of the major problems that humans need to tackle in the 21st century. Therefore, the research on the spread, prevention, and control of epidemics is quite an essential task. This paper first briefly described and analyzed the development of COVID-19 and then introduced the basic epidemic models and idealized the population in the epidemic area by dividing them into four categories (Classes S, E, I, and R). After that, it set the relevant parameters of the basic SEIR model and the modified one and worked out the relevant differential equations and iterative equations. According to the feature of the epidemic situation and the changes in the number of contacts in different units of time, the epidemic data were substituted into the iterative equations for data fitting with an R Package. Then, analysis was performed on the epidemiological features such as the transmission time and epidemic peak and the epidemic trend was evaluated. Finally, sensitivity analysis was conducted on the parameters (government control and recovery rate), and the results showed that measures such as government restrictions on travel (reducing the contacts between virus carriers and susceptible persons) can effectively control the scale of the outbreak.

Optimal Model of Emergency Medical Supplies Stowage under Traffic Control during the Initial Period of the Epidemic Based on Characteristics Analysis of COVID-19 Epidemic

In the initial stage, the epidemic area is relatively concentrated, and some traffic modes may be subject to traffic control. In this period, the timely delivery of adequate emergency medical supplies to the epidemic points will play an important role in controlling the spread of the epidemic. However, the existing emergency medical supplies loading optimization model has not taken the initial period of the epidemic as the research time nor fully considered the traffic control situation in that period. Therefore, combined with the characteristics of the initial epidemic period of COVID-19, this study establishes an optimization model for emergency medical supplies stowage at the rescue point, considering the variation in demand for different kinds of medical supplies at the epidemic point in different cycles and the impact of traffic control on the mode of transportation. The model is an integer programming model. The objective function is the least total cost, including total transportation cost and total inventory cost. The constraints include the supply limit of each medical material that can be provided by the rescue point, the transportation capacity limit of the transportation mode, the demand constraints, inventory constraints, nonnegative constraints, and integer variable constraints of various medical supplies in each cycle of the epidemic location. Finally, combining the development of the epidemic situation in Wuhan January 18–23, 2020, a case study was carried out, and the optimal combination of different transportation modes and different stowage schemes in different periods of the rescue point was obtained, which verified the feasibility and practicality of the model. The model constructed in this study can provide a theoretical reference to the optimal decision-making plan of emergency medical supplies of the implementation of traffic control during the initial period of emergency public health events.

Sleep Quality in Medical Staffs During the Outbreak of Coronavirus Disease 2019 in China: A Web-Based Cross-Sectional Study

Background: The aim of this study was to describe the sleep quality and its influencing factors among medical workers of different working statuses and staff types during the coronavirus disease 2019 (COVID-19) epidemic.Methods: Through an online questionnaire survey, all medical staffs in Xiangya Hospital were invited to complete sections on general information, the Self-Rating Scale of Sleep (SRSS), the Depression, Anxiety and Stress Scale (DASS-21), the Social Support Rating Scale (SSRS), and the Simplified Coping Style Questionnaire (CSQ).Results: A total of 4,245 respondents completed the survey. Among them, 38.7% had sleep disturbance. After matching, the SRSS scores in the staffs who were assigned to the intensive care unit (ICU) of Union Hospital in Wuhan and working in the epidemic area of Xiangya Hospital were not significantly different (P > 0.05); the SRSS scores in the battlefront staffs were significantly higher than (P < 0.05) those who were not treating patients infected with COVID-19. The SRSS scores of nurses were significantly higher than those of doctors and hospital administrators (P < 0.01). Anxiety, depression, and coping style were associated with sleep disturbance.Conclusion: The sleep quality of the medical staffs has been impaired during the epidemic period, especially among nurses, doctors, and administrators who are working on the front line. Medical institutions should strengthen psychological services and coping strategies for medical staffs.