SIR model for propagation of COVID-19 in the Paraíba's State (Brazil)

This work aims to apply the SIR-type compartmental model (Susceptible - Infected - Removed) in the evolution of Covid-19 in Paraíba's State and Campina Grande City. For that, the parameters of the model were considered to be variable during time evolution, within an appropriate range. The system of differential equations was solved numerically using the Euler method. The parameters were obtained by adjusting the model to the infected data provided by the Paraíba Health Department. According to the results obtained, the model describes the infected population well. There was a reduction in the effective reproduction number in Paraíba and the town of Campina Grande. It is noteworthy that understanding the dynamics of infection transmission and evaluating the effectiveness of control measures is crucial to assess the potential for sustained transmission to occur in new areas. The model can also be applied to describe epidemic dynamics in other regions and countries.

Spatiotemporal patterns and progression of the Delta variant of COVID-19 and their health intervention linkages in Southeast Asia

The global pandemic of COVID-19 presented an unprecedented challenge to all countries in the world, among which Southeast Asia (SEA) countries managed to maintain and mitigate the first wave of COVID-19 in 2020. However, these countries were caught in the crisis after the Delta variant was introduced to SEA, though many countries had immediately implemented non-pharmaceutical intervention (NPI) measures along with vaccination in order to contain the disease spread. To investigate the potential linkages between epidemic dynamics and public health interventions, we adopted a prospective space-time scan method to conduct spatiotemporal analysis at the district level in the seven selected countries in SEA from June 2021 to October 2021. Results reveal the spatial and temporal propagation and progression of COVID-19 risks relative to public health measures implemented by different countries. Our research benefits continuous improvements of public health strategies in preventing and containing this pandemic.

Final sizes and durations of new COVID-19 pandemic waves in Poland and Germany predicted by generalized SIR model

New waves of the COVID-19 pandemic in Europe, which began in the autumn of 2021, are a matter of great concern and the need to immediately predict the epidemic dynamics in order to assess the possible maximum values of new cases, the risk of infection and the number of deaths. The generalized SIR-model and corresponding parameter identification procedure was used to simulate and predict the dynamics of new epidemic waves in Poland and Germany. Results of calculations show that new cases in these countries will not stop to appear in 2022.

Lockdown impact on age-specific contact patterns and behaviours, France, April 2020

Background Many countries implemented national lockdowns to contain the rapid spread of SARS-CoV-2 and avoid overburdening healthcare capacity. Aim We aimed to quantify how the French lockdown impacted population mixing, contact patterns and behaviours. Methods We conducted an online survey using convenience sampling and collected information from participants aged 18 years and older between 10 April and 28 April 2020. Result Among the 42,036 survey participants, 72% normally worked outside their home, and of these, 68% changed to telework during lockdown and 17% reported being unemployed during lockdown. A decrease in public transport use was reported from 37% to 2%. Participants reported increased frequency of hand washing and changes in greeting behaviour. Wearing masks in public was generally limited. A total of 138,934 contacts were reported, with an average of 3.3 contacts per individual per day; 1.7 in the participants aged 65 years and older compared with 3.6 for younger age groups. This represented a 70% reduction compared with previous surveys, consistent with SARS-CoV2 transmission reduction measured during the lockdown. For those who maintained a professional activity outside home, the frequency of contacts at work dropped by 79%. Conclusion The lockdown affected the population's behaviour, work, risk perception and contact patterns. The frequency and heterogeneity of contacts, both of which are critical factors in determining how viruses spread, were affected. Such surveys are essential to evaluate the impact of lockdowns more accurately and anticipate epidemic dynamics in these conditions.

Phase Shift Between Age-Specific COVID-19 Incidence Curves Points to a Potential Epidemic Driver Function of Kids and Juveniles in Germany

Mutual phase shifts between three German COVID-19 incidence curves corresponding to the age classes of children, juveniles and adults, respectively, are calculated by means of delay-cross-correlations. At the country level, a phase shift of -5 weeks during the first half of the epidemic between the incidence curves corresponding to the juvenile age class and the curve corresponding to the adult class is observed. The children's incidence curve is shifted by -3 weeks with respect to the adults' curve. On the regional level of the 411 German districts (Landkreise) the distributions of observed time lags are inclined towards negative values. Regarding the incidence time series of the juvenile sub-population, 20% of the German districts exhibit negative phase shifts and only 3% show positive shifts versus the incidence curves of the adult sub-population. Similarly for the children with 6% positive shifts. Thus, children's and juveniles' epidemic activity is ahead of the adults' activity. The correlation coefficients of shifted curves are large (> 0.9 for juveniles versus adults on the country level) which indicates that aside from the phase shift the sub-populations follow a similar epidemic dynamics. Negative phase shifts of the children's incidence curves during the first and second epidemic waves are predictors for high incidences during the current fourth wave with respect to the corresponding districts.

Combining and comparing regional epidemic dynamics in Italy: Bayesian meta-analysis of compartmental models and model assessment via Global Sensitivity Analysis

During autumn 2020, Italy faced a second important SARS-CoV-2 epidemic wave. We explored the time pattern of the instantaneous reproductive number, R0(t), and estimated the prevalence of infections by region from August to December calibrating SIRD models on COVID19-related deaths, fixing at values from literature Infection Fatality Rate (IFR) and infection duration. A Global Sensitivity Analysis (GSA) was performed on the regional SIRD models. Then, we used Bayesian meta-analysis and meta-regression to combine and compare the regional results and investigate their heterogeneity. The meta-analytic R0(t) curves were similar in the Northern and Central regions, while a less peaked curve was estimated for the South. The maximum R0(t) ranged from 2.61 (North) to 2.15 (South) with an increase following school reopening and a decline at the end of October. Average temperature, urbanization, characteristics of family medicine and health care system, economic dynamism, and use of public transport could partly explain the regional heterogeneity. The GSA indicated the robustness of the regional R0(t) curves to different assumptions on IFR. The infectious period turned out to have a key role in determining the model results, but without compromising between-region comparisons.