Spatial spread of COVID-19 during the early pandemic phase in Italy

Quantifying the potential spatial spread of an infectious pathogen is key to defining effective containment and control strategies. The aim of this study is to estimate the risk of SARS-CoV-2 transmission at different distances in Italy before the first regional lockdown was imposed, identifying important sources of national spreading. To do this, we leverage on a probabilistic model applied to daily symptomatic cases retrospectively ascertained in each Italian municipality with symptom onset between January 28 and March 7, 2020. Results are validated using a multi-patch dynamic transmission model reproducing the spatiotemporal distribution of identified cases. Our results show that the contribution of short-distance ( ≤ 10 k m ) transmission increased from less than 40% in the last week of January to more than 80% in the first week of March 2020. On March 7, 2020, that is the day before the first regional lockdown was imposed, more than 200 local transmission foci were contributing to the spread of SARS-CoV-2 in Italy. At the time, isolation measures imposed only on municipalities with at least ten ascertained cases would have left uncontrolled more than 75% of spillover transmission from the already affected municipalities. In early March, national-wide restrictions were required to curb short-distance transmission of SARS-CoV-2 in Italy.

Regional Workshop for Policy Implementation Based on the Stay with Your Community Principles

A co-author of this paper had previously presented the principle of "Stay with Your Community" as a method of countermeasures against COVID-19 infection spread and have been working on its social implementation. This case study paper presents an example of activities to spread the Stay with Your Community principle to citizens and visitors in Shimoda City, Shizuoka Prefecture, in order to control the spread of COVID-19 infection. As a result, the infection cluster was successfully controlled. The authors discuss the effect of the regional workshop as a key to open the way to Organizational Citizenship Behavior of participants.

Hematology Patient Protection During the COVID-19 Pandemic in Italy: A Nationwide Nursing Survey

Background

Italy has been one of the first European countries hit by the COVID-19 pandemic, with many patients dying from severe respiratory issues, especially frail subjects. Hematology patients are generally thought to be at high risk of developing severe COVID-19-associated complications. The aim of this work was to describe the infection control measures adopted in Italian hematology settings to protect patients and health-care professionals.

Materials and Methods

On behalf of the Nursing Campus in Hematology Group, a nationwide nursing survey was conducted. Questionnaire items included general information, infection control measures, patient and health-care professional protection, information management, and participants' opinion on critical issues. Data have been analyzed by center location (Northern, Central, or Southern Italy) and by patient age (adult vs pediatric).

Results

Forty-four Italian hematology centers participated, representing 52.4% of those invited. Patients underwent nasopharyngeal swabs (93.2%) generally the day before admission (43.2%), though less frequently in Southern centers (p = 0.0377). Visitor restrictions were implemented in all centers: 65.9% barred all visitors, while 25.0% allowed visitors only for patients with specific conditions, especially in Central Italy. Deficiency of personal protective equipment, including masks (45.5%) and gloves (22.7%), was reported, although the nurses' opinion was that the emergency was nevertheless well managed to protect patients and professionals. Almost all health-care institutions (97.7%) provided recommendations on emergency management. No significant differences were found between adult and pediatric centers in terms of infection prevention and control.

Discussion

Low variability in patient protection strategies was observed, meaning that national recommendations were effective. However, some critical issues emerged regarding the management of infected health-care professionals and their contacts.

COVID-19 contact tracing in a tertiary care hospital: A retrospective chart review

Background

Contact tracing is one of the strategies used to control COVID-19 pandemic. It played an important role in the beginning to identify all contacts and minimise the spread of the infection.

Methods

A retrospective chart review was carried out of contact tracing records during the one-month period, starting from the onset of the first lockdown in India. The largest wave of 372 contacts was analysed in detail to find out the association between the result of COVID-19 test and various factors (age, gender, type of contact).

Results

A total of 372 contacts (214 males and 158 females) were traced and around 21% contacts were tested positive on COVID-19 RT-PCR test. Chi-square test didn’t find the significant difference between COVID-19 test result and proportions of male and female contacts, χ2 (1) 0.033, p = 0.855. Female positive contacts had lower mean age compared to male positive contacts, though not statistically significant, t (75) = - 1.809, p = 0.0745. No difference was found in either median or mean age of contacts with respect to COVID-19 test result. Odds of tested COVID-19 positive among household contacts much higher than community contacts, OR = 24.52, 95% CI 12.45–48.29, p < 0.05.

Conclusion

No difference was noted in the rate of contracting infection with respect to age and gender of contacts. Type of contact, household or community, significantly affected the probability of becoming infected with the coronavirus. Occupation of primary case was probably responsible for large number of contacts found positive for COVID-19.

Impact of intervention methods on COVID-19 transmission in Shenzhen

By March 31, 2020, COVID-19 had spread to more than 200 countries. Over 750,000 confirmed cases were reported, leading to more than 36,000 deaths. In this study, we analysed the efficiency of various intervention strategies to prevent infection by the virus, SARS-CoV-2, using an agent-based SEIIR model, in the fully urbanised city of Shenzhen, Guangdong Province, China. Shortening the duration from symptom onset to hospital admission, quarantining recent arrivals from Hubei Province, and letting symptomatic individuals stay at home were found to be the three most important interventions to reduce the risk of infection in Shenzhen. The ideal time window for a mandatory quarantine of arrivals from Hubei Province was between 10 January and January 17, 2020, while the ideal time window for local intervention strategies was between 15 and 22 January. The risk of infection could have been reduced by 50% if all symptomatic individuals had immediately gone to hospital for isolation, and by 35% if a 14-day quarantine for arrivals from Hubei Province had been introduced one week earlier. Intervention strategies implemented in Shenzhen were effective, and the spread of infection would be controlled even if the initial basic reproduction number had doubled. Our results may be useful for other cities when choosing their intervention strategies to prevent outbreaks of COVID-19.

COVID-19 what have we learned? The rise of social machines and connected devices in pandemic management following the concepts of predictive, preventive and personalized medicine

Objectives

Review, compare and critically assess digital technology responses to the COVID-19 pandemic around the world. The specific point of interest in this research is on predictive, preventive and personalized interoperable digital healthcare solutions. This point is supported by failures from the past, where the separate design of digital health solutions has led to lack of interoperability. Hence, this review paper investigates the integration of predictive, preventive and personalized interoperable digital healthcare systems. The second point of interest is the use of new mass surveillance technologies to feed personal data from health professionals to governments, without any comprehensive studies that determine if such new technologies and data policies would address the pandemic crisis.

Method

This is a review paper. Two approaches were used: A comprehensive bibliographic review with R statistical methods of the COVID-19 pandemic in PubMed literature and Web of Science Core Collection, supported with Google Scholar search. In addition, a case study review of emerging new approaches in different regions, using medical literature, academic literature, news articles and other reliable data sources.

Results

Most countries' digital responses involve big data analytics, integration of national health insurance databases, tracing travel history from individual's location databases, code scanning and individual's online reporting. Public responses of mistrust about privacy data misuse differ across countries, depending on the chosen public communication strategy. We propose predictive, preventive and personalized solutions for pandemic management, based on social machines and connected devices.

Solutions

The proposed predictive, preventive and personalized solutions are based on the integration of IoT data, wearable device data, mobile apps data and individual data inputs from registered users, operating as a social machine with strong security and privacy protocols. We present solutions that would enable much greater speed in future responses. These solutions are enabled by the social aspect of human-computer interactions (social machines) and the increased connectivity of humans and devices (Internet of Things).

Conclusion

Inadequate data for risk assessment on speed and urgency of COVID-19, combined with increased globalization of human society, led to the rapid spread of COVID-19. Despite an abundance of digital methods that could be used in slowing or stopping COVID-19 and future pandemics, the world remains unprepared, and lessons have not been learned from previous cases of pandemics. We present a summary of predictive, preventive and personalized digital methods that could be deployed fast to help with the COVID-19 and future pandemics.

A statistical study for impacts of environmental conditions on the rapid spread of new corona virus

The new coronavirus, COVID-19, spread quickly and causes the death for thousands of people, and a major freeze for the economy and people activities worldwide. This study made statistical analysis for the influences of the environmental conditions such as temperature, humidity, precipitation, wind, and air pollution, which may aid in spreading this virus very fast. The study also investigated statistically the impact of people customs such as smoking, drinking wine, and eating pig meat on the number of deaths among infected people. The study depicted reasons for spreading it in some places much more than others over the world. A statistical software SPSS was adopted to find a correlation among the different variables affecting the virus spread. The results exhibited a significant relationship between the suggested conditions and the virus spread. The study introduced two regression equations for expecting infected people and deaths based on the examined conditions for any region.

Rapid induction and persistence of paracrine-induced cellular antiviral states arrest viral infection spread in A549 cells

The virus/host interaction is a complex interplay between pro- and anti-viral factors that ultimately determines the spread or halt of virus infections in tissues. This interplay develops over multiple rounds of infection. The purpose of this study was to determine how cellular-level processes combine to impact the spatial spread of infection. We measured the kinetics of virus replication (VSV), antiviral paracrine signal upregulation and secretion, spatial spread of virus and paracrine antiviral signaling, and inhibition of virus production in antiviral-exposed A549 human lung epithelial cells. We found that initially infected cells released antiviral signals 4-to-7h following production of virus. However, the subsequent rapid dissemination of signal and fast induction of a robust and persistent antiviral state ultimately led to a suppression of infection spread. This work shows how cellular responses to infection and activation of antiviral responses can integrate to ultimately control infection spread across host cell populations.