Impacts of Reopening Strategies for COVID-19 Epidemic: A Modeling Study in Piedmont Region (preprint)

Background Severe acute respiratory syndrome coronavirus 2 (SARS-COV-2), the causative agent of the coronavirus disease 19 (COVID-19), is a highly transmittable virus. Since the first person-to-person transmission of SARS-CoV-2 was reported in Italy on February 21 st , 2020, the number of people infected with SARS-COV-2 increased rapidly, mainly in northern Italian regions, including Piedmont. A strict lockdown was imposed on March 21 st until May 4 th when a gradual relaxation of the restrictions started. In this context, computational models and computer simulations are one of the available research tools that epidemiologists can exploit to understand the spread of the diseases and to evaluate social measures to counteract, mitigate or delay the spread of the epidemic. Methods This study presents an extended version of the Susceptible-Exposed-Infected-Removed-Susceptible (SEIRS) model accounting for population age structure. The infectious population is divided into three sub-groups: (i) undetected infected individuals, (ii) quarantined infected individuals and (iii) hospitalized infected individuals. Moreover, the strength of the government restriction measures and the related population response to these are explicitly represented in the model. Results The proposed model allows us to investigate different scenarios of the COVID-19 spread in Piedmont and the implementation of different infection-control measures and testing approaches. The results show that the implemented control measures have proven effective in containing the epidemic, mitigating the potential dangerous impact of a large proportion of undetected cases. We also forecast the optimal combination of individual-level measures and community surveillance to contain the new wave of COVID-19 spread after the re-opening work and social activities. Conclusions Our model is an effective tool useful to investigate different scenarios and to inform policy makers about the potential impact of different control strategies. This will be crucial in the upcoming months, when very critical decisions about easing control measures will need to be taken.

COVID-19-like symptoms and their relation to SARS-CoV-2 epidemic in children and adults of an Italian birth cohort (preprint)

Background A number of cases positive for SARS-CoV-2 escape surveillance systems, especially in the first epidemic waves and/or when the number of cases becomes too large to allow complete diagnostic coverage.  Methods During the first SARS-CoV-2 epidemic wave hitting Italy in the spring 2020, mothers participating in an Italian NINFEA birth cohort were invited to complete an online questionnaire on COVID-19-like symptoms in the household. We estimated the population prevalence of COVID-19-like symptoms in children and adults, assessed their geographical correlation with the cumulative number of COVID-19 cases by province, analysed their clustering within families, and estimated their sensitivity, positive predictive value (PPV) and negative predictive value (NPV) for COVID-19 diagnosis in individuals tested for SARS-CoV-2.Results Information was collected on 3184 households, 6133 adults, and 5751 children. In the period March-April 2020, 55.4% of the NINFEA families had at least one member with at least one COVID-19-like symptom. There was a strong geographical correlation between the population cumulative incidence of COVID-19 and the prevalence of muscle pain, fatigue, low-grade fever, and breathing difficulties in adults (Spearman’s rho ≥0.70). Having at least one family member with a COVID-19 diagnosis, compared with none tested for SARS-CoV-2, was associated with an increased prevalence ratio (PR) of almost all COVID-19-like symptoms in adults, and only of low-grade fever (37-37.5°C; PR 5.27; 95% confidence intervals: 2.37 to 11.74) and anosmia/dysgeusia in children. Among adults with COVID-19 diagnosis, fatigue, muscle pain, and fever had a sensitivity ≥70%. In individuals tested for SARS-CoV-2, with a 16.6% prevalence of COVID-19, breathing difficulties and nausea/vomiting had the highest PPVs, with point estimates close to 60%, and with NPVs close to 90%.Conclusions The geographical prevalence of COVID-19-like symptoms in adults may inform on local disease clusters, while certain symptoms in family members of confirmed COVID-19 cases could help identify the intra-familial spread of the virus and its further propagation in the community. Low-grade fever is frequent in children with at least one household member with COVID-19 and possibly indicates child infection. 

Is death from Covid-19 a multistep process? (preprint)

Covid-19 death has a different relationship with age than is the case for other severe respiratory pathogens. The Covid-19 death rate increases exponentially with age, and the main risk factors are age itself, as well as having underlying conditions such as hypertension, diabetes, cardiovascular disease, severe chronic respiratory disease and cancer. Furthermore, the almost complete lack of deaths in children suggests that infection alone is not sufficient to cause death; rather, one must have gone through a number of changes, either as a result of undefined aspects of aging, or as a result of chronic disease. These characteristics of Covid-19 death are consistent with the multistep model of disease, a model which has primarily been used for cancer, and more recently for amyotrophic lateral sclerosis (ALS). We applied the multi-step model to data on Covid-19 case fatality rates (CFRs) from China, South Korea, Italy, Spain and Japan. In all countries we found that a plot of ln (CFR) against ln (age) was approximately linear with a slope of about 5. As a comparison, we also conducted similar analyses for selected other respiratory diseases. SARS showed a similar log-log age-pattern to that of Covid-19, albeit with a lower slope, whereas seasonal and pandemic influenza showed quite different age-patterns. Thus, death from Covid-19 and SARS appears to follow a distinct age-pattern, consistent with a multistep model of disease that in the case of Covid-19 is probably defined by comorbidities and age producing immune-related susceptibility. Identification of these steps would be potentially important for prevention and therapy for SARS-COV-2 infection.