The impact of control and mitigation strategies during the second wave of coronavirus infections in Spain and Italy

Determinants of COVID-19 Infection Among Employees of an Italian Financial Institution

BACKGROUND

Understanding the trend of the severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) is becoming crucial. Previous studies focused on predicting COVID-19 trends, but few papers have considered models for disease estimation and progression based on large real-world data.

METHODS

We used de-identified data from 60,938 employees of a major financial institution in Italy with daily COVID-19 status information between 31 March 2020 and 31 August 2021. We consider six statuses: (i) concluded case, (ii) confirmed case, (iii) close contact, (iv) possible-probable contact, (v) possible contact, and (vi) no-COVID-19 or infection. We conducted a logistic regression to assess the odds ratio (OR) of transition to confirmed COVID-19 case at each time point. We also fitted a general model for disease progression via the multi-state transition probability model at each time point, with lags of 7 and 15 days.

RESULTS

Employment in a branch versus in a central office was the strongest predictor of case or contact status, while no association was detected with gender or age. The geographic prevalence of possible-probable contacts and close contacts was predictive of the subsequent risk of confirmed cases. The status with the highest probability of becoming a confirmed case was concluded case (12%) in April 2020, possible-probable contact (16%) in November 2020, and close contact (4%) in August 2021. The model based on transition probabilities predicted well the rate of confirmed cases observed 7 or 15 days later.

CONCLUSION

Data from industry-based surveillance systems may effectively predict the risk of subsequent infection.

SARS-CoV-2 infection in meat and poultry workers after the "first wave" (Summer 2020): a cross-sectional study on knowledge, attitudes, practices (KAP) of Italian occupational physicians

BACKGROUND AND AIM

This cross-sectional study assessed knowledge, attitudes and practices (KAP) of Italian Occupational Physicians (OPs) on Coronavirus disease 2019 (COVID-19) among meat/poultry processing plant workers (MPWs) (Summer season 2020).

METHODS

Data were collected through an online questionnaire including demographic characteristics, and items about COVID-19-related KAP in MPWs. A logistic regression was modelled in order to characterize explanatory variables of the outcome variable of having any professional experience as OP in meat/poultry processing industry.

RESULTS

A total of 424 OPs (mean age 49.0 ± 9.1years; 49.5% males) participated into the survey. Despite a generally good level of knowledge on SARS-CoV-2 pandemic, OPs having professional experience with MPWs failed to recognize any increased risk for COVID-19 (Odds Ratio [OR] 0.162; 95% Confidence intervals [95%CI] 0.039-0.670), and were less likely to recommend periodical tests via nasal swabs (OR 0.168, 95%CI 0.047-0.605). On the contrary, they identified socioeconomic status of MPWs as a risk factor (OR 5.686, 95%CI 1.413-22.881), recommending cleaning interventions on changing rooms and canteens (OR 16.090, 95%CI 1.099-259.244).

CONCLUSIONS

In conclusion, we reported a diffuse underestimation of the risk for COVID-19, that was alarmingly higher among professionals who should be more familiar with the specific requirements of MPWs. Some significant knowledge gaps were also clearly identified, stressing the opportunity for tailored educative interventions (www.actabiomedica.it).

Effectiveness of the booster dose of COVID-19 vaccine in the Basque Country during the sixth wave: A nationwide cohort study

The aim of the study was to assess the effect of a booster dose of COVID-19 vaccine on the rates of hospital ward and intensive care unit (ICU) admissions around the time of emergence of the Omicron variant in the Basque Country. A retrospective cohort population-based study was conducted. The population with any records related to COVID-19 vaccination up to 28 February 2022 was classified into four cohorts by vaccination status. For every cohort, the hospital ward and ICU admission rates were calculated for each day between November 2021 and February 2022. Generalized linear models with a negative binomial distribution were used to estimate the age-adjusted hospitalization rate ratio of the cohort of individuals who had received a booster compared to the other cohorts. The age-adjusted rates of hospital ward and ICU admissions were 70.4 % and 72.0 % lower, respectively, in the fully vaccinated plus booster group compared to the fully vaccinated but no booster group. Analysing changes in the 14-day admission incidence rates showed that as the prevalence of the Omicron variant increased, the corresponding rate ratios decreased. The immunity acquired with the booster dose allowed the hospital network to meet all the demand for hospitalization during a period of high incidence of COVID-19, despite the fact that vaccine protection decreased as the prevalence of the Omicron variant increased.

COVID-19 outbreaks analysis in the Valencian Region of Spain in the prelude of the third wave

Introduction

The COVID-19 pandemic has led to unprecedented social and mobility restrictions on a global scale. Since its start in the spring of 2020, numerous scientific papers have been published on the characteristics of the virus, and the healthcare, economic and social consequences of the pandemic. However, in-depth analyses of the evolution of single coronavirus outbreaks have been rarely reported.

Methods

In this paper, we analyze the main properties of all the tracked COVID-19 outbreaks in the Valencian Region between September and December of 2020. Our analysis includes the evaluation of the origin, dynamic evolution, duration, and spatial distribution of the outbreaks.

Results

We find that the duration of the outbreaks follows a power-law distribution: most outbreaks are controlled within 2 weeks of their onset, and only a few last more than 2 months. We do not identify any significant differences in the outbreak properties with respect to the geographical location across the entire region. Finally, we also determine the cluster size distribution of each infection origin through a Bayesian statistical model.

Discussion

We hope that our work will assist in optimizing and planning the resource assignment for future pandemic tracking efforts.

Excess Mortality on Italian Small Islands during the SARS-CoV-2 Pandemic: An Ecological Study

Small islands have been considered at an advantage when dealing with infectious diseases, including COVID-19, but the evidence is still lacking. Crude mortality rates (CMRs) and excess mortality rates (EMRs) were calculated for 35 municipalities on the Italian small islands for 2020 and 2021, and the corresponding estimates were compared to those of the parent provinces and the national estimates. Notification rates for COVID-19 were retrieved, but detailed data at the municipality level were not available. A relatively low CMR (1.069 per 100 per year, 95% confidence interval [95% CI] 0.983−1.164) was identified in 2020, compared to 1.180, 95% CI 1.098−1.269 for 2021. EMRs of small islands ranged between −25.6% and +15.6% in 2020, and between −13.0% and +20.9% in 2021, with an average gain of +0.3% (95% CI −5.3 to +5.8) for the entirety of the assessed timeframe, and no substantial differences between 2020 and 2021 (pooled estimates of −4.1%, 95% CI −12.3 to 4.1 vs. 4.6%, 95% CI −3.1 to 12.4; p = 0.143). When dealing with COVID-19 notification rates, during the first wave, parent provinces of Italian small islands exhibited substantially lower estimates than those at the national level. Even though subsequent stages of the pandemic (i.e., second, third, and fourth waves) saw a drastic increase in the number of confirmed cases and CMR, estimates from small islands remained generally lower than those from parent provinces and the national level. In regression analysis, notification rates and mortality in the parent provinces were the main effectors of EMRs in the small islands (β = 0.469 and β = 22.768, p < 0.001 and p = 0.007, respectively). Contrarily, the management of incident cases in hospital infrastructures and ICUs was characterized as a negative predictor for EMR (β = −11.208, p = 0.008, and −59.700, p = 0.003, respectively). In summary, the study suggests a potential role of small geographical and population size in strengthening the effect of restrictive measures toward countering the spread and mortality rate of COVID-19.