The impact of travelling on the COVID-19 infection cases in Germany

Patterns of case fatality and hospitalization duration among nearly 1 million hospitalized COVID-19 patients covered by Iran Health Insurance Organization (IHIO) over two years of pandemic: An analysis of associated factors

BACKGROUND

Different populations and areas of the world experienced diverse COVID-19 hospitalization and mortality rates. Claims data is a systematically recorded source of hospitalized patients' information that could be used to evaluate the disease management course and outcomes. We aimed to investigate the hospitalization and mortality patterns and associated factors in a huge sample of hospitalized patients.

METHODS

In this retrospective registry-based study, we utilized claim data from the Iran Health Insurance Organization (IHIO) consisting of approximately one million hospitalized patients across various hospitals in Iran over a 26-month period. All records in the hospitalization dataset with ICD-10 codes U07.1/U07.2 for clinically/laboratory confirmed COVID-19 were included. In this study, a case referred to one instance of a patient being hospitalized. If a patient experienced multiple hospitalizations within 30 days, those were aggregated into a single case. However, if hospitalizations had longer intervals, they were considered independent cases. The primary outcomes of study were general and intensive care unit (ICU) hospitalization periods and case fatality rate (CFR) at the hospital. Besides, various demographic and hospitalization-associated factors were analyzed to derive the associations with study outcomes using accelerated failure time (AFT) and logistic regression models.

RESULTS

A total number of 1 113 678 admissions with COVID-19 diagnosis were recorded by IHIO during the study period, defined as 917 198 cases, including 51.9% females and 48.1% males. The 61-70 age group had the highest number of cases for both sexes. Among defined cases, CFR was 10.36% (95% CI: 10.29-10.42). The >80 age group had the highest CFR (26.01% [95% CI: 25.75-26.27]). The median of overall hospitalization and ICU days were 4 (IQR: 3-7) and 5 (IQR: 2-8), respectively. Male patients had a significantly higher risk for mortality both generally (odds ratio (OR) = 1.36 [1.34-1.37]) and among ICU admitted patients (1.12 [1.09-1.12]). Among various insurance funds, Foreign Citizens had the highest risk of death both generally (adjusted OR = 2.06 [1.91-2.22]) and in ICU (aOR = 1.71 [1.51-1.92]). Increasing age groups was a risk of longer hospitalization, and the >80 age group had the highest risk for overall hospitalization period (median ratio = 1.52 [1.51-1.54]) and at ICU (median ratio = 1.17 [1.16-1.18]). Considering Tehran as the reference province, Sistan and Balcuchestan (aOR = 1.4 [1.32-1.48]), Alborz (aOR = 1.28 [1.22-1.35]), and Khorasan Razavi (aOR = 1.24 [1.20-1.28]) were the provinces with the highest risk of mortality in hospitalized patients.

CONCLUSION

Hospitalization data unveiled mortality and duration associations with variables, highlighting provincial outcome disparities in Iran. Using enhanced registry systems in conjunction with other studies, empowers policymakers with evidence for optimizing resource allocation and fortifying healthcare system resilience against future health challenges.

Modelling the spatial spread of COVID-19 in a German district using a diffusion model

In this study, we focus on modeling the local spread of COVID-19 infections. As the pandemic continues and new variants or future pandemics can emerge, modelling the early stages of infection spread becomes crucial, especially as limited medical data might be available initially. Therefore, our aim is to gain a better understanding of the diffusion dynamics on smaller scales using partial differential equation (PDE) models. Previous works have already presented various methods to model the spatial spread of diseases, but, due to a lack of data on regional or even local scale, few actually applied their models on real disease courses in order to describe the behaviour of the disease or estimate parameters. We use medical data from both the Robert-Koch-Institute (RKI) and the Birkenfeld district government for parameter estimation within a single German district, Birkenfeld in Rhineland-Palatinate, during the second wave of the pandemic in autumn 2020 and winter 2020-21. This district can be seen as a typical middle-European region, characterized by its (mainly) rural nature and daily commuter movements towards metropolitan areas. A basic reaction-diffusion model used for spatial COVID spread, which includes compartments for susceptibles, exposed, infected, recovered, and the total population, is used to describe the spatio-temporal spread of infections. The transmission rate, recovery rate, initial infected values, detection rate, and diffusivity rate are considered as parameters to be estimated using the reported daily data and least square fit. This work also features an emphasis on numerical methods which will be used to describe the diffusion on arbitrary two-dimensional domains. Two numerical optimization techniques for parameter fitting are used: the Metropolis algorithm and the adjoint method. Two different methods, the Crank-Nicholson method and a finite element method, which are used according to the requirements of the respective optimization method are used to solve the PDE system. This way, the two methods are compared and validated and provide similar results with good approximation of the infected in both the district and the respective sub-districts.

Humoral immune response to SARS-CoV-2 and endemic coronaviruses in urban and indigenous children in Colombia

BACKGROUND

Although anti-SARS-CoV-2 humoral immune responses and epidemiology have been extensively studied, data gaps remain for certain populations such as indigenous people or children especially in low- and middle-income countries. To address this gap, we evaluated SARS-CoV-2 seroprevalence and humoral immunity towards the parental B.1 strain, local SARS-CoV-2 variants, and endemic coronaviruses in children from Colombia from March to April 2021.

METHODS

We performed a cross-sectional seroprevalence study with 80 children from Bogotá and expanded our analysis by comparing results with an independent observational study of 82 children from the Wiwa community living in the north-eastern Colombian territories. Antibody IgG titers towards SARS-CoV-2 and the endemic coronaviruses as well as ACE2 binding inhibition as a proxy for neutralization towards several SARS-CoV-2 variants were analyzed using two multiplex-based immunoassays.

RESULTS

While we find seroprevalence estimates of 21.3% in children from Bogotá, seroprevalence is higher with 34.1% in Wiwa children. We observe a robust induction of antibodies towards the surface-exposed spike protein, its S1-, S2- and receptor-binding-subdomains in all SARS-CoV-2 seropositive children. Only nucleocapsid-specific IgG is significantly lower in the indigenous participants. ACE2 binding inhibition is low for all SARS-CoV-2 variants examined. We observe a dominance of NL63 S1 IgG levels in urban and indigenous children which suggests an early exposure to this respiratory virus independent of living conditions and geographic location. SARS-CoV-2 seropositivity does not correlate with antibody levels towards any of the four endemic coronaviruses indicating the absence of cross-protective immunity.

CONCLUSIONS

Overall, antibody titers, but in particular ACE2 binding inhibition are low within Colombian samples, requiring further investigation to determine any potential clinical significance.

Does tourism affect the long term course of COVID-19 pandemic in a country of destination? Evidence from a popular Greek island in 2020 where control measures were implemented

Greece opened its points of entry on July 1, 2020, with specific guidelines for travellers arriving by sea, air or land. The aim of this article is to examine the effect of tourism on the long term course of the Coronavirus Disease 2019 (COVID-19) pandemic during the pre-vaccination era (June to December 2020) on the popular Greek island of Crete. To achieve this, a cross-sectional serosurvey, repeated at monthly intervals, was conducted to compare the seroprevalence in Crete with seroprevalence in the mainland of Greece. Crete welcomed nearly 2,000,000 travellers during the 2020 summer season. Left-over serum samples were collected and obtained from public and private laboratories located in Greece, including the island of Crete. These samples were tested for the presence of anti-SARS-CoV-2 IgG antibodies. A total of 55,938 samples were collected, 3,785 of which originated from Crete. In Crete, the seroprevalence ranged between 0% (June 2020) and 2.58% (December 2020), while the corresponding seroprevalence in Greece was 0.19% and 10.75%, respectively. We identified 4.16 times lower seropositivity in Crete (2.58%) in comparison with the mainland of Greece (10.75%) during December 2020. Moreover, the monthly infection fatality rate (IFR) in Crete was calculated at 0.09%, compared with 0.21% in mainland Greece for December 2020. The island of Crete presented more than four times lower seroprevalence than the mainland of Greece, despite being a highly attractive tourist destination. This evidence supports the idea that tourism may not have affected the long term course of the COVID-19 pandemic in Greece. However, due to contradicting results from previous studies, further investigation is needed.

COVID-19 vaccination in the mass vaccination center: clinical practice and effectiveness analysis

Objectives

Mass vaccination campaigns can rapidly increase the vaccination rate for the COVID-19 vaccine, the establishment of mass vaccination centers is indispensable. At the beginning of March 2021, China began to carry out COVID-19 vaccination activities nationwide. Here, we aimed to evaluate the criteria established by mass vaccination centers, COVID-19 vaccination experience, the incidence of adverse events following immunization and opinions.

Methods

We describe the layout and functioning of Nan'an District mass vaccination center, the working mechanism, experience and effectiveness. Distribution of COVID-19 vaccine vaccination and adverse events following immunization reported in the mass vaccination center of Nan'an District were evaluated.

Results

From March 26, 2021 to April 28, 2022, the mass vaccination center has inoculated about 381,364 doses of COVID-19 vaccine to the population. The study found that the incidence of adverse events following immunization (AEFI) was very low (1.04/100000). The chances of having AEFI were significantly higher in COVID-19 vaccine (CHO cell) than COVID-19 vaccine (Vero cell).

Conclusion

The mass vaccination center was running successfully. It was effective and safe, providing vaccination services and increasing COVID-19 vaccination rates among the population. The experience of the mass vaccination center for COVID-19 in China can provide a reference for other countries and regions to carry out COVID-19 vaccination.

Lag-time effects of vaccination on SARS-CoV-2 dynamics in German hospitals and intensive-care units

Background

The Efficacy and effectiveness of vaccination against SARS-CoV-2 have clearly been shown by randomized trials and observational studies. Despite these successes on the individual level, vaccination of the population is essential to relieving hospitals and intensive care units. In this context, understanding the effects of vaccination and its lag-time on the population-level dynamics becomes necessary to adapt the vaccination campaigns and prepare for future pandemics.

Methods

This work applied a quasi-Poisson regression with a distributed lag linear model on German data from a scientific data platform to quantify the effects of vaccination and its lag times on the number of hospital and intensive care patients, adjusting for the influences of non-pharmaceutical interventions and their time trends. We separately evaluated the effects of the first, second and third doses administered in Germany.

Results

The results revealed a decrease in the number of hospital and intensive care patients for high vaccine coverage. The vaccination provides a significant protective effect when at least approximately 40% of people are vaccinated, whatever the dose considered. We also found a time-delayed effect of the vaccination. Indeed, the effect on the number of hospital patients is immediate for the first and second doses while for the third dose about 15 days are necessary to have a strong protective effect. Concerning the effect on the number of intensive care patients, a significant protective response was obtained after a lag time of about 15-20 days for the three doses. However, complex time trends, e.g. due to new variants, which are independent of vaccination make the detection of these findings challenging.

Conclusion

Our results provide additional information about the protective effects of vaccines against SARS-CoV-2; they are in line with previous findings and complement the individual-level evidence of clinical trials. Findings from this work could help public health authorities efficiently direct their actions against SARS-CoV-2 and be well-prepared for future pandemics.