One Year of the COVID-19 Pandemic in Galicia: A Global View of Age-Group Statistics during Three Waves

A population structure-sensitive mathematical model assessing the effects of vaccination during the third surge of COVID-19 in Italy

We provide a non-autonomous mathematical model to describe some of the most relevant parameters associated to the COVID-19 pandemic, such as daily and cumulative deaths, active cases, and cumulative incidence, among others. We will take into consideration the ways in which people from four different age ranges react to the virus. Using an appropriate transmission function, we estimate the impact of the third surge of COVID-19 in Italy. Also, we assess two different vaccination programmes. In one of them, a single shot is administered to all citizens over 16 years old before second shots are available. In the second model, first and second shots are administered to each citizen within, approximately, 20 days of time-gap.

Modelling the impact of reopening schools in the UK in early 2021 in the presence of the alpha variant and with roll-out of vaccination against SARS-CoV-2

Following the resurgence of the COVID-19 epidemic in the UK in late 2020 and the emergence of the alpha (also known as B117) variant of the SARS-CoV-2 virus, a third national lockdown was imposed from January 4, 2021. Following the decline of COVID-19 cases over the remainder of January 2021, the question of when and how to reopen schools became an increasingly pressing one in early 2021. This study models the impact of a partial national lockdown with social distancing measures enacted in communities and workplaces under different strategies of reopening schools from March 8, 2021 and compares it to the impact of continual full national lockdown remaining until April 19, 2021. We used our previously published agent-based model, Covasim, to model the emergence of the alpha variant over September 1, 2020 to January 31, 2021 in presence of Test, Trace and Isolate (TTI) strategies. We extended the model to incorporate the impacts of the roll-out of a two-dose vaccine against COVID-19, with 200,000 daily vaccine doses prioritised by age starting with people 75 years or older, assuming vaccination offers a 95% reduction in disease acquisition risk and a 30% reduction in transmission risk. We used the model, calibrated until January 25, 2021, to simulate the impact of a full national lockdown (FNL) with schools closed until April 19, 2021 versus four different partial national lockdown (PNL) scenarios with different elements of schooling open: 1) staggered PNL with primary schools and exam-entry years (years 11 and 13) returning on March 8, 2021 and the rest of the schools years on March 15, 2020; 2) full-return PNL with both primary and secondary schools returning on March 8, 2021; 3) primary-only PNL with primary schools and exam critical years (years 11 and 13) going back only on March 8, 2021 with the rest of the secondary schools back on April 19, 2021 and 4) part-rota PNL with both primary and secondary schools returning on March 8, 2021 with primary schools remaining open continuously but secondary schools on a two-weekly rota-system with years alternating between a fortnight of face-to-face and remote learning until April 19, 2021. Across all scenarios, we projected the number of new daily cases, cumulative deaths and effective reproduction number R until April 30, 2021. Our calibration across different scenarios is consistent with alpha variant being around 60% more transmissible than the wild type. We find that strict social distancing measures, i.e. national lockdowns, were essential in containing the spread of the virus and controlling hospitalisations and deaths during January and February 2021. We estimated that a national lockdown over January and February 2021 would reduce the number of cases by early March to levels similar to those seen in October 2020, with R also falling and remaining below 1 over this period. We estimated that infections would start to increase when schools reopened, but found that if other parts of society remain closed, this resurgence would not be sufficient to bring R above 1. Reopening primary schools and exam critical years only or having primary schools open continuously with secondary schools on rotas was estimated to lead to lower increases in cases and R than if all schools opened. Without an increase in vaccination above the levels seen in January and February, we estimate that R could have increased above 1 following the reopening of society, simulated here from April 19, 2021. Our findings suggest that stringent measures were integral in mitigating the increase in cases and bringing R below 1 over January and February 2021. We found that it was plausible that a PNL with schools partially open from March 8, 2021 and the rest of the society remaining closed until April 19, 2021 would keep R below 1, with some increase evident in infections compared to continual FNL until April 19, 2021. Reopening society in mid-April, without an increase in vaccination levels, could push R above 1 and induce a surge in infections, but the effect of vaccination may be able to control this in future depending on the transmission blocking properties of the vaccines.

Clinical-epidemiologic variation in patients treated in the first and second wave of COVID-19 in Lambayeque, Peru: A cluster analysis

OBJECTIVES

To identify differences in the clinical and epidemiologic characteristics of patients during the first and second waves of the COVID-19 pandemic at the EsSalud Lambayeque health care network, Peru.

METHODS

An analytical cross-sectional study of 53,912 patients enrolled during the first and second waves of COVID-19 was conducted. Cluster analysis based on clustering large applications (CLARA) was applied to clinical-epidemiologic data presented at the time of care. The two pandemic waves were compared using clinical-epidemiologic data from epidemiologic surveillance.

RESULTS

Cluster analysis identified four COVID-19 groups with a characteristic pattern. Cluster 1 included the largest number of participants in both waves, and the participants were predominantly female. Cluster 2 included patients with gastrointestinal, respiratory, and systemic symptoms. Cluster 3 was the "severe" cluster, characterized by older adults and patients with dyspnea or comorbidities (cardiovascular, diabetes, obesity). Cluster 4 included asymptomatic, pregnant, and less severe patients. We found differences in all clinical-epidemiologic characteristics according to the cluster to which they belonged.

CONCLUSION

Using cluster analysis, we identified characteristic patterns in each group. Respiratory, gastrointestinal, dyspnea, anosmia, and ageusia symptoms were higher in the second COVID-19 wave than the first COVID-19 wave.

Area-level socioeconomic deprivation, non-national residency, and Covid-19 incidence: A longitudinal spatiotemporal analysis in Germany

BACKGROUND

Socioeconomic conditions affect the dynamics of the Covid-19 pandemic. We analysed the association between area-level socioeconomic deprivation, proportion of non-nationals, and incidence of Covid-19 infections in Germany.

METHODS

Using linked nationally representative data at the level of 401 German districts from three waves of infection (January-2020 to May-2021), we fitted Bayesian spatiotemporal models to assess the association between socioeconomic deprivation, and proportion of non-nationals with Covid-19 incidence, controlling for age, sex, vaccination coverage, settlement structure, and spatial and temporal effects. We estimated risk ratios (RR) and corresponding 95% credible intervals (95% CrI). We further examined the deprivation domains (education, income, occupation), interactions between deprivation, sex and the proportion of non-nationals, and explored potential pathways from deprivation to Covid-19 incidence.

FINDINGS

Covid-19 incidence risk was 15% higher (RR=1·15, 95%-CrI=1·06-1·24) in areas classified with the highest deprivation quintile (Q5) compared to the least deprived areas (Q1). Medium-low (Q2), medium (Q3), and medium-high (Q4) deprived districts showed 6% (1·06, 1·00-1·12), 8% (1·08, 1·01-1·15), and 5% (1·05, 0·98-1·13) higher risk, respectively, compared to the least deprived. Districts with higher proportion of non-nationals showed higher incidence risk compared to districts with lowest proportion, but the association weakened across the three waves. During the first wave, an inverse association was observed with highest incidence risk in least deprived areas (Q1). Deprivation interacted with sex, but not with the proportion of non-nationals.

INTERPRETATION

Socioeconomic deprivation, and proportion of non-nationals are independently associated with the incidence of Covid-19. Regional planning of non-pharmaceutical interventions and vaccination strategies would benefit from consideration of area-level deprivation and non-national residency.

FUNDING

The study was funded by the German Ministry of Health (ZMV I 1 - 25 20 COR 410).

Health system impacts of SARS-CoV − 2 variants of concern: a rapid review

Background

As of November 25th 2021, four SARS-CoV − 2 variants of concern (VOC: Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), and Delta (B.1.617.2)) have been detected. Variable degrees of increased transmissibility of the VOC have been documented, with potential implications for hospital and health system capacity and control measures. This rapid review aimed to provide a synthesis of evidence related to health system responses to the emergence of VOC worldwide.

Methods

Seven databases were searched up to September 27, 2021, for terms related to VOC. Titles, abstracts, and full-text documents were screened independently by two reviewers. Data were extracted independently by two reviewers using a standardized form. Studies were included if they reported on at least one of the VOC and health system outcomes.

Results

Of the 4877 articles retrieved, 59 studies were included, which used a wide range of designs and methods. Most of the studies reported on Alpha, and all except two reported on impacts for capacity planning related to hospitalization, intensive care admissions, and mortality. Most studies (73.4%) observed an increase in hospitalization, but findings on increased admission to intensive care units were mixed (50%). Most studies (63.4%) that reported mortality data found an increased risk of death due to VOC, although health system capacity may influence this. No studies reported on screening staff and visitors or cohorting patients based on VOC.

Conclusion

While the findings should be interpreted with caution as most of the sources identified were preprints, evidence is trending towards an increased risk of hospitalization and, potentially, mortality due to VOC compared to wild-type SARS-CoV − 2. There is little evidence on the need for, and the effect of, changes to health system arrangements in response to VOC transmission.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-07847-0.

Age Dependent Epidemic Modeling of COVID-19 Outbreak in Kuwait, France, and Cameroon

Revisiting the classical model by Ross and Kermack-McKendrick, the Susceptible−Infectious−Recovered (SIR) model used to formalize the COVID-19 epidemic, requires improvements which will be the subject of this article. The heterogeneity in the age of the populations concerned leads to considering models in age groups with specific susceptibilities, which makes the prediction problem more difficult. Basically, there are three age groups of interest which are, respectively, 0−19 years, 20−64 years, and >64 years, but in this article, we only consider two (20−64 years and >64 years) age groups because the group 0−19 years is widely seen as being less infected by the virus since this age group had a low infection rate throughout the pandemic era of this study, especially the countries under consideration. In this article, we proposed a new mathematical age-dependent (Susceptible−Infectious−Goneanewsusceptible−Recovered (SIGR)) model for the COVID-19 outbreak and performed some mathematical analyses by showing the positivity, boundedness, stability, existence, and uniqueness of the solution. We performed numerical simulations of the model with parameters from Kuwait, France, and Cameroon. We discuss the role of these different parameters used in the model; namely, vaccination on the epidemic dynamics. We open a new perspective of improving an age-dependent model and its application to observed data and parameters.

COVID-19 vaccination program in the mainland of China: a subnational descriptive analysis on target population size and current progress

BACKGROUND

China is facing substantial risks of imported coronavirus disease 2019 (COVID-19) cases and a domestic resurgence in the long run, and COVID-19 vaccination is expected to be the long-lasting solution to end the pandemic. We aim to estimate the size of the target population for COVID-19 vaccination at the provincial level in the mainland of China, and summarize the current progress of vaccination programs, which could support local governments in the timely determination and adjustment of vaccination policies and promotional measures.

METHODS

We conducted a descriptive study of the entire population in the mainland of China, between December 2020 and August 2021. By extracting provincial-stratified data from publicly available sources, we estimated the size of priority target groups for vaccination programs, and further characterized the ongoing vaccination program at the provincial level, including the total doses administered, the coverage rate, and the vaccination capacity needed to achieve the target coverage of 80% by the end of 2021. We used R (version 4.1.0) to complete the descriptive statistics.

RESULTS

The size of the target population shows large differences among provinces, ranging from 3.4 million to 108.4 million. As of 31 August, 2021, the speed of vaccine roll-out differs considerably as well, with the highest coverage occurring in Beijing and Shanghai, where 88.5% and 79.1% of the population has been fully vaccinated, respectively. In 22 of 31 provincial-level administrative divisions (PLADs), more than 70% of the population was administered at least one dose by August. With the current vaccination capacity, the target of 80% coverage could be achieved by 2021 in 28 PLADs.

CONCLUSIONS

Disparities exist in the target population size and vaccination progress across provinces in the mainland of China. China has made great strides in the vaccination speed since roll-out, and could basically achieve the targeted vaccine coverage.