Factors associated with the spatial heterogeneity of the first wave of COVID-19 in France: a nationwide geo-epidemiological study

Health Care Resource Use and Total Mortality After Hospital Admission for Severe COVID-19 Infections During the Initial Pandemic Wave in France: Descriptive Study

BACKGROUND

Little is known about post-hospital health care resource use (HRU) of patients admitted for severe COVID-19, specifically for the care of patients with postacute COVID-19 syndrome (PACS).

OBJECTIVE

A list of HRU domains and items potentially related to PACS was defined, and potential PACS-related HRU (PPRH) was compared between the pre- and post-COVID-19 periods, to identify new outpatient care likely related to PACS.

METHODS

A retrospective cohort study was conducted with the French National Health System claims data (SNDS). All patients hospitalized for COVID-19 between February 1, 2020, and June 30, 2020 were described and investigated for 6 months, using discharge date as index date. Patients who died during index stay or within 30 days after discharge were excluded. PPRH was assessed over the 5 months from day 31 after index date to end of follow-up, that is, for the post-COVID-19 period. For each patient, a pre-COVID-19 period was defined that covered the same calendar time in 2019, and pre-COVID-19 PPRH was assessed. Post- or pre- ratios (PP ratios) of the percentage of users were computed with their 95% CIs, and PP ratios>1.2 were considered as "major HRU change."

RESULTS

The final study population included 68,822 patients (median age 64.8 years, 47% women, median follow-up duration 179.3 days). Altogether, 23% of the patients admitted due to severe COVID-19 died during the hospital stay or within the 6 months following discharge. A total of 8 HRU domains were selected to study PPRH: medical visits, technical procedures, dispensed medications, biological analyses, oxygen therapy, rehabilitation, rehospitalizations, and nurse visits. PPRs showed novel outpatient care in all domains and in most items, without specificity, with the highest ratios observed for the care of thoracic conditions.

CONCLUSIONS

Patients hospitalized for severe COVID-19 during the initial pandemic wave had high morbi-mortality. The analysis of HRU domains and items most likely to be related to PACS showed that new care was commonly initiated after discharge but with no specificity, potentially suggesting that any impact of PACS was part of the overall high HRU of this population after hospital discharge. These purely descriptive results need to be completed with methods for controlling for confusion bias through subgroup analyses.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05073328; https://clinicaltrials.gov/ct2/show/NCT05073328.

Data-driven mathematical modeling approaches for COVID-19: A survey

In this review, we successively present the methods for phenomenological modeling of the evolution of reported and unreported cases of COVID-19, both in the exponential phase of growth and then in a complete epidemic wave. After the case of an isolated wave, we present the modeling of several successive waves separated by endemic stationary periods. Then, we treat the case of multi-compartmental models without or with age structure. Eventually, we review the literature, based on 260 articles selected in 11 sections, ranging from the medical survey of hospital cases to forecasting the dynamics of new cases in the general population. This review favors the phenomenological approach over the mechanistic approach in the choice of references and provides simulations of the evolution of the number of observed cases of COVID-19 for 10 states (California, China, France, India, Israel, Japan, New York, Peru, Spain and United Kingdom).

Reviving health mediation during the COVID-19 crisis and beyond: an implementation study in deprived neighbourhoods of Marseille, France

Introduction

In 2020, during France's COVID-19 response, healthcare professionals from a hospital and an association initiated health mediation interventions in Marseille's vulnerable neighbourhoods, funded by the regional health authorities. This mixed method research evaluates the CORHESAN program that lasted until June 2022.

Methods

We examined CORHESAN documents and reports, conducted interviews, and analysed activity data, comparing it to the COVID-19 hotspots identified on a weekly basis at the neighbourhood level, using generalised linear mixed models (GLMMs).

Results

CORHESAN was implemented by a team of up to nine health mediators, six private nurses hired on an ad hoc basis, supervised by a general coordinator and two part-time medical and nursing coordinators. Multiple partnerships were established with shelters, associations, social-housing landlords and local institutions. The team accompanied 6,253 people affected by COVID-19 or contact in the practical implementation of their isolation and contact tracing. Of the 5,180 nasopharyngeal samples for RT-PCR and 1,875 for antigenic testing: 12% were taken at home and 27% in partner facilities in the targeted neighbourhoods; 32% were taken from symptomatic patients and 30% in the context of contact tracing; and 40% were positive. Multiple awareness sessions on prevention methods and distributions of personal protection kits and self-diagnostic tests were conducted in the streets, in shelters, in associations or at home. A total of 5,929 doses of COVID-19 vaccine were administered in a walk-in vaccination centre, at temporary street vaccination posts, during operations at partner facilities, or during home-visits to patients with limited autonomy. GLMMs showed that the intervention significantly targeted its testing interventions in neighbourhoods with socioeconomic disadvantage and/or past under-testing (adjusted odds ratio (aOR), 2.75 [1.50-5.00]) and those with high hotspot level (aOR for level-3 versus level-0, 1.83 [1.24-2.71]).

Discussion

The pandemic emphasised the potential of health mediation interventions to address health disparities. Building on this, a new program began in July 2022, aiming at enhancing cancer screening and vaccinations in deprived areas of Marseille. Evaluations are ongoing to assess its activities and impact, and provide evidence to future implementation initiatives.

Spatial spread of COVID-19 during the early pandemic phase in Italy

Quantifying the potential spatial spread of an infectious pathogen is key to defining effective containment and control strategies. The aim of this study is to estimate the risk of SARS-CoV-2 transmission at different distances in Italy before the first regional lockdown was imposed, identifying important sources of national spreading. To do this, we leverage on a probabilistic model applied to daily symptomatic cases retrospectively ascertained in each Italian municipality with symptom onset between January 28 and March 7, 2020. Results are validated using a multi-patch dynamic transmission model reproducing the spatiotemporal distribution of identified cases. Our results show that the contribution of short-distance ( ≤ 10 k m ) transmission increased from less than 40% in the last week of January to more than 80% in the first week of March 2020. On March 7, 2020, that is the day before the first regional lockdown was imposed, more than 200 local transmission foci were contributing to the spread of SARS-CoV-2 in Italy. At the time, isolation measures imposed only on municipalities with at least ten ascertained cases would have left uncontrolled more than 75% of spillover transmission from the already affected municipalities. In early March, national-wide restrictions were required to curb short-distance transmission of SARS-CoV-2 in Italy.

Evolution of the profiles of new psychotropic drug users before and during the COVID-19 crisis: an original longitudinal approach through multichannel sequence analysis using the French health-care database

The COVID-19 pandemic has had a substantial impact on mental health. An increase in the use of anxiolytic, hypnotic, and antidepressant drugs has been highlighted in France, but with no information at the individual level (trajectories) or concerning patient characteristics. The objective of this study was to describe the profile of new psychotropic drug users since the beginning of the pandemic. We formed two historical cohorts using the Pays-de-la-Loire regional component of the National Health Data System (SNDS): a "COVID-19 crisis cohort" (2020-2021) and a "control cohort" (2018-2019). We analyzed reimbursements for psychotropic medications (anxiolytics, antidepressants, hypnotics, mood stabilizers, and antipsychotics) using a multichannel sequence analysis and performed clustering analysis of sequences. The proportion of new consumers of psychotropic drugs was higher in the COVID-19 crisis cohort (18.0%) than that in the control cohort (16.0%). In the COVID-19 cohort, three clusters of psychotropic drug users were identified, whereas four clusters were identified in the control cohort. A time lag in treatment initiation was observed in the COVID-19 crisis cohort (September) compared with the control cohort (July). This study is one of the first to analyze the profile of psychotropic treatment users during the COVID-19 crisis. Our analysis sheds light on changes in patterns of psychotropic drug use during the COVID-19 pandemic, possibly associated with changes in prescribing conditions and mental health conditions during the crisis. This study also provides an example of the application of an innovative longitudinal analysis methodology in the field of pharmacoepidemiology.

Deaths induced by compassionate use of hydroxychloroquine during the first COVID-19 wave: an estimate

BACKGROUND

During the first wave of COVID-19, hydroxychloroquine (HCQ) was used off-label despite the absence of evidence documenting its clinical benefits. Since then, a meta-analysis of randomised trials showed that HCQ use was associated with an 11% increase in the mortality rate. We aimed to estimate the number of HCQ-related deaths worldwide.

METHODS AND FINDINGS

We estimated the worldwide in-hospital mortality attributable to HCQ use by combining the mortality rate, HCQ exposure, number of hospitalised patients, and the increased relative risk of death with HCQ. The mortality rate in hospitalised patients for each country was calculated using pooled prevalence estimated by a meta-analysis of published cohorts. The HCQ exposure was estimated using median and extreme estimates from the same systematic review. The number of hospitalised patients during the first wave was extracted from dedicated databases. The systematic review included 44 cohort studies (Belgium: k = 1, France: k = 2, Italy: k = 12, Spain: k = 6, Turkey: k = 3, USA: k = 20). HCQ prescription rates varied greatly from one country to another (range 16-84%). Overall, using median estimates of HCQ use in each country, we estimated that 16,990 HCQ-related in-hospital deaths (range 6267-19256) occurred in the countries with available data. The median number of HCQ-related deaths in Belgium, Turkey, France, Italy, Spain, and the USA was 240 (range not estimable), 95 (range 92-128), 199 (range not estimable), 1822 (range 1170-2063), 1895 (range 1475-2094) and 12739 (3244- 15570), respectively.

CONCLUSIONS

Although our estimates are limited by their imprecision, these findings illustrate the hazard of drug repurposing with low-level evidence.

Public Health Response Measures for COVID-19 in Kazakhstan

The article describes measures developed to counter the spread of coronavirus infection in the Republic of Kazakhstan. The first cases of coronavirus disease 2019 (COVID-19) in Kazakhstan were detected on March 13, 2020, among people who arrived from Germany. After declaring the state of emergency in the country, the Ministry of Healthcare of the Republic of Kazakhstan began to formulate and implement a comprehensive package of measures aimed at slowing down and stopping the transmission of infection, preventing outbreaks, ensuring optimal care for all patients, especially the seriously ill, minimizing the negative impact of the pandemic on health systems, social services, and economic activities. Developed set of restrictive measures was approved by the Country Office of Word Health Organization (WHO) in Kazakhstan, being later adapted by the European Union (EU) countries and applied in Kyrgyzstan. In addition, article identifies Kazakhstan's experience in creating epidemiological surveillance systems, studying virus mutations, and the clinical aspects of dealing with it to combat the infection. It also indicates the impact of the epidemic on health-care workers and the development of measures to protect them, strengthening infection prevention, and control in medical organizations.

Forecasting the Endemic/Epidemic Transition in COVID-19 in Some Countries: Influence of the Vaccination

OBJECTIVE

The objective of this article is to develop a robust method for forecasting the transition from endemic to epidemic phases in contagious diseases using COVID-19 as a case study.

METHODS

Seven indicators are proposed for detecting the endemic/epidemic transition: variation coefficient, entropy, dominant/subdominant spectral ratio, skewness, kurtosis, dispersion index and normality index. Then, principal component analysis (PCA) offers a score built from the seven proposed indicators as the first PCA component, and its forecasting performance is estimated from its ability to predict the entrance in the epidemic exponential growth phase.

RESULTS

This score is applied to the retro-prediction of endemic/epidemic transitions of COVID-19 outbreak in seven various countries for which the first PCA component has a good predicting power.

CONCLUSION

This research offers a valuable tool for early epidemic detection, aiding in effective public health responses.

Relationships between the COVID-19 lockdown, socioeconomic factors and acute coronary syndrome hospitalisations in France

INTRODUCTION

Worldwide, the COVID-19 pandemic has been associated with an overall drop in acute coronary syndrome (ACS) hospitalizations. Additionally, there is a well-known association between ACS and socioeconomic status. This study aims to assess the COVID-19 effect on ACS admissions in France during the first national lockdown and investigate the factors associated with its spatial heterogeneity.

MATERIALS AND METHODS

In this retrospective study, we used the French hospital discharge database (PMSI) to estimate ACS admission rates in all public and private hospitals in 2019 and 2020. A negative binomial regression explored the nationwide change in ACS admissions during lockdown compared with 2019. A multivariate analysis explored the factors associated with the ACS admission incidence rate ratio (IRR, 2020 incidence rate/2019 incidence rate) variation at the county level.

RESULTS

We found a significant but geographically heterogeneous nationwide reduction in ACS admissions during lockdown (IRR 0·70 [0·64-0·76]). After adjustment for cumulative COVID-19 admissions and the ageing index, a higher share of people on short-term working arrangements during lockdown at the county level was associated with a lower IRR, while a higher share of individuals with a high school degree and a higher density of acute care beds were associated with a higher ratio.

CONCLUSIONS

During the first national lockdown, there was an overall decrease in ACS admissions. Local provision of inpatient care and socioeconomic determinants linked to occupation were independently associated with the variation in hospitalizations.

Social deprivation and SARS-CoV-2 testing: a population-based analysis in a highly contrasted southern France region

Background

Testing was the cornerstone of the COVID-19 epidemic response in most countries until vaccination became available for the general population. Social inequalities generally affect access to healthcare and health behaviors, and COVID-19 was rapidly shown to impact deprived population more drastically. In support of the regional health agency in Provence-Alpes-Côte d'Azur (PACA) in South-Eastern France, we analyzed the relationship between testing rate and socio-demographic characteristics of the population, to identify gaps in testing coverage and improve targeting of response strategies.

Methods

We conducted an ecological analysis of SARS-CoV-2/COVID-19 testing rate in the PACA region, based on data aggregated at the finest spatial resolution available in France (IRIS) and by periods defined by public health implemented measures and major epidemiological changes. Using general census data, population density, and specific deprivation indices, we used principal component analysis followed by hierarchical clustering to define profiles describing local socio-demographic characteristics. We analyzed the association between these profiles and testing rates in a generalized additive multilevel model, adjusting for access to healthcare, presence of a retirement home, and the age profile of the population.

Results

We identified 6 socio-demographic profiles across the 2,306 analyzed IRIS spatial units: privileged, remote, intermediate, downtown, deprived, and very deprived (ordered by increasing social deprivation index). Profiles also ranged from rural (remote) to high density urban areas (downtown, very deprived). From July 2020 to December 2021, we analyzed SARS-CoV-2/COVID-19 testing rate over 10 periods. Testing rates fluctuated strongly but were highest in privileged and downtown areas, and lowest in very deprived ones. The lowest adjusted testing rate ratios (aTRR) between privileged (reference) and other profiles occurred after implementation of a mandatory healthpass for many leisure activities in July 2021. Periods of contextual testing near Christmas displayed the largest aTRR, especially during the last periods of 2021 after the end of free convenience testing for unvaccinated individuals.

Conclusion

We characterized in-depth local heterogeneity and temporal trends in testing rates and identified areas and circumstances associated with low testing rates, which the regional health agency targeted specifically for the deployment of health mediation activities.

Place of death in France: impact of the first wave (March-May 2020) of the Covid-19 epidemic

BACKGROUND

The Covid-19 epidemic entailed a major public health issue in France challenging the efficiency of the public health system. The distribution of deaths by place in France may have been affected by the epidemic and mitigation actions. This article presents mortality rate ratios by place of death in France during the first lockdown (17 March - 10 May, 2020) of the Covid-19 epidemic.

METHODS

We considered five places of death recorded in death certificates. Deaths in 2020 were compared to deaths from 2015 to 2019. We employed quasi-Poisson regressions in order to stablish mortality rate ratios (MRR) during the Covid-19 epidemic, for all-cause and non-Covid-19 deaths. Analysis was conducted in Metropolitan France, and for three groups of regions defined according to the intensity of the first COVID-19 epidemic wave.

RESULTS

A significant increase in all-cause and non-COVID-19 mortality at home was observed for all age groups. Also, an increase in mortality was observed in nursing homes, mostly due to Covid-19. Non-covid-19 mortality in public hospitals decreased significantly in all the country. These trends were mainly observed for cancers.

CONCLUSIONS

Overall mortality increased during the first wave of the Covid-19 epidemic. Most Covid-19 deaths took place in public hospitals and nursing homes at old ages. There was a displacement of non-Covid-19 mortality from public hospitals to home and nursing homes, particularly in the most highly exposed area. Among hypotheses to explain such a displacement, population avoidance of hospital care, or redeployment of hospital activity in this emergent context can be cited. Further analysis is needed to understand the reasons of the increase in non-Covid-19 mortality in nursing homes and at home.

Impact of COVID-19 lockdowns on postoperative morbidity after hepatectomy: A propensity-score matching study on a national French database

BACKGROUND

The impact of the SARS-CoV-2 pandemic on managing liver malignancies worldwide is unknown. This study aimed to determine the impact of lockdowns on patient clinical pathways and postoperative morbi-mortality.

METHODS

This study evaluated all adults' hospital stays for liver tumors between 2019 and 2021 from the national French discharge database. The primary outcome was the clinical pathway, especially surgical care and postoperative outcomes, between patients admitted during COVID-19 lockdown periods (lockdown group) and during the same periods of 2019 and 2021 (control groups).

RESULTS

The overall population included 58,508 patients: 18,907 patients in the lockdown group, 20,045 in the 2019 control group, and 19,556 in the 2021 control group. Surgical activity decreased by 11.6% during lockdowns, with 1,514 (8.0%) of patients in the lockdown group treated by surgery, 1,514 (8.6%) in the 2019 control group (P < .001), and 1,466 (7.4%) in the 2021 control group. Chemotherapy was considered more during the lockdowns (P < .001). More patients were operated in small-volume centers during the lockdowns (34% vs 32% vs 32%, P = .034), and fewer were hospitalized in highly populated regions (P < .001). Postoperative morbidity (47% vs 47% vs 47%, P = .90) and mortality (3.3% vs 3.6% vs 3.1%, P = .80) were comparable in the 3 periods, with no influence of lockdowns on morbidity (risk ratio = 0.94, 95% confidence interval = 0.81-1.09, P = .40) or mortality (odds ratio = 1.12, 95% confidence interval = 0.72-1.74, P = .6). Postoperative pulmonary (17% vs 13%, P = .024) and septic complications (20% vs 15%, P = .022) were significantly higher during the first lockdown compared to the second.

CONCLUSION

This study provides a French overview of liver malignancy management during the COVID-19 pandemic. Moreover, surgical activity decreased by 11.6% in high-volume centers, with no impact on postoperative morbidity and mortality.

Impact of policy response on health protection and economic recovery in OECD and BRIICS countries during the early stages of the COVID-19 pandemic

OBJECTIVES

During the early stages of the COVID-19 pandemic, the full reopening of the economy typically accelerated viral transmission. This study aims to determine whether policy response could contribute to the dual objective of both reducing the spread of the epidemic and revitalising economic activities.

STUDY DESIGN

This is a longitudinal study of Organization for Economic Cooperation and Development (OECD) and Brazil, Russia, India, Indonesia, China, and South Africa (BRIICS) from the first quarter (Q1) of 2020 to the same period of 2021.

METHODS

From a health-economic perspective, this study established a framework to illustrate the following outcomes: suppression-prosperity, outbreak-stagnancy, outbreak-prosperity and suppression-stagnancy scenarios. Multinomial logistic models were used to analyse the associations between policy response with both the pandemic and the economy. The study further examined two subtypes of policy response, stringency/health measures and economic support measures, separately. The probabilities of the different scenarios were estimated.

RESULTS

Economic prosperity and epidemic suppression were significantly associated with policy response. The effects of policy response on health-economic scenarios took the form of inverse U-shapes with the increase in intensity. 'Leptokurtic', 'bimodal' and 'long-tailed' curves demonstrated the estimated possibilities of suppression-prosperity, outbreak-prosperity and suppression-stagnancy scenarios, respectively. In addition, stringency/health policies followed the inverted U-shaped pattern, whereas economic support policies showed a linear pattern.

CONCLUSIONS

It was possible to achieve the dual objective of economic growth and epidemic control simultaneously, and the effects of policy response were shaped like an inverse U. These findings provide a new perspective for balancing the economy with public health during the early stages of the pandemic.

Geo-epidemiological approach of the COVID-19 pandemic in France and in Europe for public health policies

The spread of the COVID-19 pandemic has shown great heterogeneity between countries that merits investigation. There is a need to better highlight the variability in the pandemic trajectories in different geographic areas. By using openly available data from 'GitHub' COVID-19 dataset for Europe and from the official dataset of France for the period 2020 to 2021, I present the three COVID-19 waves in France and Europe in maps. The epidemic trends across areas display different evolutions for different time periods. National and European public health authorities will be able to improve allocation of resources for more effective public health measures based on geo-epidemiological analyses.

Changes in health communication in the age of COVID-19: A study on the dissemination of preprints to the public

Introduction

Preprints have become an important tool for meeting the challenges of health communication in the context of COVID-19. They allow scientists to disseminate their results more quickly due to the absence of a peer review process. Preprints have been well-received by scientists, however, there have been concerns about the exposure of wider public audiences to preprints due in part to this lack of peer review.

Methods

The aim of this study is to examine the dissemination of preprints on medRxiv and bioRxiv during the COVID-19 pandemic using content analysis and statistical analysis.

Results

Our findings show that preprints have played an unprecedented role in disseminating COVID-19-related science results to the public.

Discussion

While the overall media coverage of preprints is unsatisfactory, digital native news media performed better than legacy media in reporting preprints, which means that we could make the most of digital native media to improve health communication. This study contributes to understanding how science communication has evolved in response to the COVID-19 pandemic and provides some practical recommendations.

Data-driven multiscale dynamical framework to control a pandemic evolution with non-pharmaceutical interventions

Before the availability of vaccines, many countries have resorted multiple times to drastic social restrictions to prevent saturation of their health care system, and to regain control over an otherwise exponentially increasing COVID-19 pandemic. With the advent of data-sharing, computational approaches are key to efficiently control a pandemic with non-pharmaceutical interventions (NPIs). Here we develop a data-driven computational framework based on a time discrete and age-stratified compartmental model to control a pandemic evolution inside and outside hospitals in a constantly changing environment with NPIs. Besides the calendrical time, we introduce a second time-scale for the infection history, which allows for non-exponential transition probabilities. We develop inference methods and feedback procedures to successively recalibrate model parameters as new data becomes available. As a showcase, we calibrate the framework to study the pandemic evolution inside and outside hospitals in France until February 2021. We combine national hospitalization statistics from governmental websites with clinical data from a single hospital to calibrate hospitalization parameters. We infer changes in social contact matrices as a function of NPIs from positive testing and new hospitalization data. We use simulations to infer hidden pandemic properties such as the fraction of infected population, the hospitalisation probability, or the infection fatality ratio. We show how reproduction numbers and herd immunity levels depend on the underlying social dynamics.

Concerted and multidisciplinary management of COVID-19 drug therapies during the first two epidemic waves in a tertiary hospital in Marseille, France: Results of the PHARMA-COVID study

OBJECTIVES

To evaluate the impact of local therapeutic recommendation updates made by the COVID multidisciplinary consultation meeting (RCP) at the Hôpital Européen Marseille (HEM) through the description of the drug prescriptions for COVID-19 during the first two waves of the epidemic.

METHODS

This retrospective observational study analysed data from the hospital's pharmaceutical file. We included all patients hospitalized for COVID-19 between February 1, 2020 and January 21, 2021 and extracted specific anti-COVID-19 therapies (ST) from computerized patient record, as well as patients' demographic characteristics, comorbidities and outcome. The evolution of ST prescriptions during the study period was described and put into perspective with the updates of local recommendations made during the first (V1, from 2/24/2020 to 7/27/2020), and second (V2, from 7/28/2020 to 1/21/2021) epidemic waves.

RESULTS

A total of 607 COVID-19 hospitalized patients, 197 during V1 and 410 during V2. Their mean age was 65 years-old, and they presented frequent comorbidities. In total, 93% of hospitalized patients received ST: anticoagulants (90%), glucocorticoids (39%) mainly during V2 (49% vs 17%, P<0.001), and azithromycin (30%) mainly during V1 (71% vs 10%, P<0.001). Lopinavir/ritonavir and hydroxychloroquine were prescribed to 17 and 7 inpatients, respectively, and only during V1. Remdesivir was never administered. A total of 22 inpatients were enrolled into clinical trials.

CONCLUSIONS

The effective dissemination of evidence-based and concerted recommendations seems to have allowed an optimized management of COVID-19 drug therapies in the context of this emerging infection with rapidly evolving therapeutic questions.

Why were some countries more successful than others in curbing early COVID-19 mortality impact? A cross-country configurational analysis

Why was there considerable variation in initial COVID-19 mortality impact across countries? Through a configurational lens, this paper examines which configurations of five conditions-a delayed public-health response, past epidemic experience, proportion of elderly in population, population density, and national income per capita-influence early COVID-19 mortality impact measured by years of life lost (YLL). A fuzzy-set qualitative comparative analysis (fsQCA) of 80 countries identifies four distinctive pathways associated with high YLL rate and four other different pathways leading to low YLL rate. Results suggest that there is no singular "playbook"-a set of policies that countries can follow. Some countries failed differently, whereas others succeeded differently. Countries should take into account their situational contexts to adopt a holistic response strategy to combat any future public-health crisis. Regardless of the country's past epidemic experience and national income levels, a speedy public-health response always works well. For high-income countries with high population density or past epidemic experience, they need to take extra care to protect elderly populations who may otherwise overstretch healthcare capacity.

Predisposing factors for admission to intensive care units of patients with COVID-19 infection-Results of the German nationwide inpatient sample

Background

Intensive care units (ICU) capacities are one of the most critical determinants in health-care management of the COVID-19 pandemic. Therefore, we aimed to analyze the ICU-admission and case-fatality rate as well as characteristics and outcomes of patient admitted to ICU in order to identify predictors and associated conditions for worsening and case-fatality in this critical ill patient-group.

Methods

We used the German nationwide inpatient sample to analyze all hospitalized patients with confirmed COVID-19 diagnosis in Germany between January and December 2020. All hospitalized patients with confirmed COVID-19 infection during the year 2020 were included in the present study and were stratified according ICU-admission.

Results

Overall, 176,137 hospitalizations of patients with COVID-19-infection (52.3% males; 53.6% aged ≥70 years) were reported in Germany during 2020. Among them, 27,053 (15.4%) were treated in ICU. COVID-19-patients treated on ICU were younger [70.0 (interquartile range (IQR) 59.0-79.0) vs. 72.0 (IQR 55.0-82.0) years, P < 0.001], more often males (66.3 vs. 48.8%, P < 0.001), had more frequently cardiovascular diseases (CVD) and cardiovascular risk-factors with increased in-hospital case-fatality (38.4 vs. 14.2%, P < 0.001). ICU-admission was independently associated with in-hospital death [OR 5.49 (95% CI 5.30-5.68), P < 0.001]. Male sex [OR 1.96 (95% CI 1.90-2.01), P < 0.001], obesity [OR 2.20 (95% CI 2.10-2.31), P < 0.001], diabetes mellitus [OR 1.48 (95% CI 1.44-1.53), P < 0.001], atrial fibrillation/flutter [OR 1.57 (95% CI 1.51-1.62), P < 0.001], and heart failure [OR 1.72 (95% CI 1.66-1.78), P < 0.001] were independently associated with ICU-admission.

Conclusion

During 2020, 15.4% of the hospitalized COVID-19-patients were treated on ICUs with high case-fatality. Male sex, CVD and cardiovascular risk-factors were independent risk-factors for ICU admission.

Time-dependent risk of COVID-19 death with overwhelmed health-care capacity in Japan, 2020-2022

BACKGROUND

It has been descriptively argued that the case fatality risk (CFR) of coronavirus disease (COVID-19) is elevated when medical services are overwhelmed. The relationship between CFR and pressure on health-care services should thus be epidemiologically explored to account for potential epidemiological biases. The purpose of the present study was to estimate the age-dependent CFR in Tokyo and Osaka over time, investigating the impact of caseload demand on the risk of death.

METHODS

We estimated the time-dependent CFR, accounting for time delay from diagnosis to death. To this end, we first determined the time distribution from diagnosis to death, allowing variations in the delay over time. We then assessed the age-dependent CFR in Tokyo and Osaka. In Osaka, the risk of intensive care unit (ICU) admission was also estimated.

RESULTS

The CFR was highest among individuals aged 80 years and older and during the first epidemic wave from February to June 2020, estimated as 25.4% (95% confidence interval [CI] 21.1 to 29.6) and 27.9% (95% CI 20.6 to 36.1) in Tokyo and Osaka, respectively. During the fourth wave of infection (caused by the Alpha variant) in Osaka the CFR among the 70s and ≥ 80s age groups was, respectively, 2.3 and 1.5 times greater than in Tokyo. Conversely, despite the surge in hospitalizations, the risk of ICU admission among those aged 80 and older in Osaka decreased. Such time-dependent variation in the CFR was not seen among younger patients < 70 years old. With the Omicron variant, the CFR among the 80s and older in Tokyo and Osaka was 3.2% (95% CI 3.0 to 3.5) and 2.9% (95% CI 2.7 to 3.1), respectively.

CONCLUSION

We found that without substantial control, the CFR can increase when a surge in cases occurs with an identifiable elevation in risk-especially among older people. Because active treatment options including admission to ICU cannot be offered to the elderly with an overwhelmed medical service, the CFR value can potentially double compared with that in other areas of health care under less pressure.

Structural and Managerial Risk Factors for COVID-19 Occurrence in French Nursing Homes

BACKGROUND

Nursing home (NH) residents accounted for half of the deaths during the 2020 spring wave of the coronavirus disease 2019 (COVID-19) epidemic in France. Our objective was to identify structural and managerial factors associated with COVID-19 outbreaks in NHs.

METHODS

We conducted in July 2020 a retrospective study by questionnaire addressed to NH directors in the Brittany region of France. The questions related to structural characteristics of the establishment, human resources, and crisis management decisions. The primary endpoint was the occurrence of at least one confirmed case of COVID-19 among residents between March 1, 2020 and May 31, 2020. The secondary endpoint was total mortality during this period. We used multivariate regressions to identify factors associated with these outcomes.

RESULTS

Responses were collected from 231 NHs hosting 20,881 residents, representing a participation rate of 47%. In 24 (10%) NHs, at least one resident presented confirmed COVID-19. NHs often implemented stringent protective measures, with 65% of them choosing to confine residents to their rooms. In multivariate analysis, factors associated with a reduced risk of case occurrence were in-room meal service, early ban of family visits, and daily access to an outdoor space. No association was found between mortality and the factors studied. Our results show an early and strict implementation of lockdown measures, with good epidemiological results in a context of shortage of personal protective equipment (PPE) and non-vaccination. Nevertheless, it raises ethical questions concerning respect of residents' wellbeing and rights.

CONCLUSION

Cessation of communal dining seems to be the main measure likely to be effective in preventive terms. It does not seem that room lockdown and cessation of group activities should be recommended, particularly if mask wearing is possible.

Impact of spatiotemporal heterogeneity in COVID-19 disease surveillance on epidemiological parameters and case growth rates

SARS-CoV-2 case data are primary sources for estimating epidemiological parameters and for modelling the dynamics of outbreaks. Understanding biases within case-based data sources used in epidemiological analyses is important as they can detract from the value of these rich datasets. This raises questions of how variations in surveillance can affect the estimation of epidemiological parameters such as the case growth rates. We use standardised line list data of COVID-19 from Argentina, Brazil, Mexico and Colombia to estimate delay distributions of symptom-onset-to-confirmation, -hospitalisation and -death as well as hospitalisation-to-death at high spatial resolutions and throughout time. Using these estimates, we model the biases introduced by the delay from symptom-onset-to-confirmation on national and state level case growth rates (rt) using an adaptation of the Richardson-Lucy deconvolution algorithm. We find significant heterogeneities in the estimation of delay distributions through time and space with delay difference of up to 19 days between epochs at the state level. Further, we find that by changing the spatial scale, estimates of case growth rate can vary by up to 0.13 d^-1. Lastly, we find that states with a high variance and/or mean delay in symptom-onset-to-diagnosis also have the largest difference between the rt estimated from raw and deconvolved case counts at the state level. We highlight the importance of high-resolution case-based data in understanding biases in disease reporting and how these biases can be avoided by adjusting case numbers based on empirical delay distributions. Code and openly accessible data to reproduce analyses presented here are available.

Spatiotemporal heterogeneity of SARS-CoV-2 diffusion at the city level using geographically weighted Poisson regression model: The case of Bologna, Italy

This paper aimed to analyse the spatio-temporal patterns of the diffusion of SARS-CoV-2, the virus causing coronavirus 2019 (COVID-19, in the city of Bologna, the capital and largest city of the Emilia-Romagna Region in northern Italy. The study took place from February 1st, 2020 to November 20th, 2021 and accounted for space, sociodemographic characteristics and health conditions of the resident population. A second goal was to derive a model for the level of risk of being infected by SARS-CoV-2 and to identify and measure the place-specific factors associated with the disease and its determinants. Spatial heterogeneity was tested by comparing global Poisson regression (GPR) and local geographically weighted Poisson regression (GWPR) models. The key findings were that different city areas were impacted differently during the first three epidemic waves. The area-to-area influence was estimated to exert its effect over an area with 4.7 km radius. Spatio-temporal heterogeneity patterns were found to be independent of the sociodemographic and the clinical characteristics of the resident population. Significant single-individual risk factors for detected SARS-CoV-2 infection cases were old age, hypertension, diabetes and co-morbidities. More specifically, in the global model, the average SARS-CoV-2 infection rate decreased 0.93-fold in the 21-65 years age group compared to the >65 years age group, whereas hypertension, diabetes, and any other co-morbidities (present vs absent), increased 1.28-, 1.39- and 1.15-fold, respectively. The local GWPR model had a better fit better than GPR. Due to the global geographical distribution of the pandemic, local estimates are essential for mitigating or strengthening security measures.

Comparison of Clinical Features, Complete Blood Count Parameters, and Outcomes between Two Distinct Waves of COVID-19: A Monocentric Report from Italy

BACKGROUND

Since the beginning of the SARS-CoV-2 pandemic, the ability to predict the trajectory of the disease has represented a major challenge for clinicians. There is recent evidence that complete blood cell count (CBC)-derived inflammation indexes have predictive value in COVID-19. We aimed to describe any changes in the clinical features, CBC-derived ratios, and outcomes of patients admitted to our hospital across two temporally distinct waves.

METHODS

We retrospectively assessed and compared the clinical characteristics and blood cell count values of patients hospitalized during the second and fourth waves of COVID-19, and explored any outcome differences in terms of the level of respiratory support required and transfer to intensive care.

RESULTS

We observed that fourth-wave patients were older, less male-predominant, and carried more comorbidities compared to the second-wave patients but, nevertheless, experienced more favorable outcomes. A strong internal correlation was documented for both waves between outcomes and CBC-derived ratios, with the fourth-wave cases displaying lower admission values of the neutrophil-to-lymphocyte ratio (NLR), derived NLR (dNLR), platelet-to-lymphocyte ratio (PLR), and systemic inflammation index (SII). No significant differences were found for lymphocyte-to-monocyte ratio (LMR), systemic inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI).

CONCLUSIONS

We observed that both admission values of CBC-derived indexes and adverse respiratory outcomes decreased from the second to the fourth wave of COVID-19. These data represent a contribution to the existing knowledge on the role of CBC-derived indexes as a potential tool to help clinicians to quickly differentiate in-hospital patients at increased risk of serious illness and death.

Transmission of SARS-CoV-2 during indoor clubbing events: A clustered randomized, controlled, multicentre trial protocol

Introduction

The SARS-CoV-2 pandemic led to the implementation of several non-pharmaceutical interventions (NPIs), from closings of bars and restaurants to curfews and lockdowns. Vaccination campaigns started hoping it could efficiently alleviate NPI. The primary objective of the "Indoor Transmission of COVID-19" (ITOC) study is to determine among a fully vaccinated population the relative risk of SARS-CoV-2 transmission during one indoor clubbing event. Secondary objectives are to assess the transmission of other respiratory viruses, risk exposure, and attitudes toward COVID-19 vaccination, health pass, and psychological impact of indoor club closing.

Methods and analysis

Four thousand four hundred healthy volunteers aged 18-49 years and fully vaccinated will be included in Paris region. The intervention is an 8-hour indoor clubbing event with no masks, no social distance, maximum room capacity, and ventilation. A reservation group of up to 10 people will recruit participants, who will be randomized 1:1 to either the experimental group (2,200 volunteers in two venues with capacities of 1,000 people each) or the control group (2,200 volunteers asked not to go to the club). All participants will provide a salivary sample on the day of the experiment and 7 days later. They also will answer several questionnaires. Virological analyses include polymerase chain reaction (PCR) of salivary samples and air of the venue, investigating SARS-CoV-2 and 18 respiratory viruses.

Ethics and dissemination

Ethical clearance was first obtained in France from the institutional review board (Comité de Protection des Personnes Ile de France VII - CPP), and the trial received clearance from the French National Agency for Medicines and Health Products (Agence National de Sécurité du Médicament - ANSM). The trial is supported and approved by The Agence Nationale Recherche sur le SIDA, les hépatites et maladies émergences (ANRS-MIE). Positive, negative, and inconclusive results will be published in peer-reviewed scientific journals.

Trial registration number

IDR-CB 2021-A01473-38. Clinicaltrial.gov, identifier: NCT05311865.

What have we learned about socioeconomic inequalities in the spread of COVID-19? A systematic review

This article aims to provide a better understanding of the associations between groups of socioeconomic variables and confirmed cases of COVID-19. The focus is on cross-continental differences of reported positive, negative, unclear, or no associations. A systematic review of the literature is conducted on the Web of Science and SCOPUS databases. Our search identifies 314 eligible studies published on or before 31 December 2021. We detect nine groups of frequently used socioeconomic variables and results are presented by region of the world (Africa, Asia, Europe, Middle East, North American and South America). The review expands to describe the most used statistical and modelling techniques as well as inclusion of additional dimensions such as demographic, healthcare weather and mobility. Meanwhile findings agree on the generalized positive impact of population density, per capita GDP and urban areas on transmission of infections, contradictory results have been found concerning to educational level and income.

Risks of infection, hospital and ICU admission, and death from COVID-19 in people with asthma: systematic review and meta-analyses

OBJECTIVES

To determine if and to what degree asthma may predispose to worse COVID-19 outcomes in order to inform treatment and prevention decisions, including shielding and vaccine prioritisation.

DESIGN

Systematic review and meta-analysis.

SETTING

Electronic databases were searched (October 2020) for clinical studies reporting at least one of the following stratified by asthma status: risk of infection with SARS-CoV-2; hospitalisation, intensive care unit (ICU) admission or mortality with COVID-19.

PARTICIPANTS

Adults and children who tested positive for or were suspected to have COVID-19.

MAIN OUTCOME MEASURES

Main outcome measures were the following stratified by asthma status: risk of infection with SARS-CoV-2; hospitalisation, ICU admission or mortality with COVID-19. We pooled odds ratios (ORs) and presented these with 95% confidence intervals (CI). Certainty was assessed using GRADE (Grading of Recommendations, Assessment, Development and Evaluations).

RESULTS

30 (n=112 420) studies were included (12 judged high quality, 15 medium, 3 low). Few provided indication of asthma severity. Point estimates indicated reduced risks in people with asthma for all outcomes, but in all cases the evidence was judged to be of very low certainty and 95% CIs all included no difference and the possibility of increased risk (death: OR 0.90, 95% CI 0.72 to 1.13, I²=58%; hospitalisation: OR 0.95, 95% CI 0.71 to 1.26; ICU admission: OR 0.96, 95% CI 0.75 to 1.24). Findings on hospitalisation are also limited by substantial unexplained statistical heterogeneity. Within people with asthma, allergic asthma was associated with less COVID-19 risk and concurrent chronic obstructive pulmonary disease was associated with increased risk. In some studies, corticosteroids were associated with increased risk, but this may reflect increased risk in people with more severe asthma.

CONCLUSIONS

Though absence of evidence of a clear association between asthma and worse outcomes from COVID-19 should not be interpreted as evidence of absence, the data reviewed indicate that risks from COVID-19 in people with asthma, as a whole, may be less than originally anticipated.

[Management of the COVID-19 epidemic in the carrier battle group (January-April 2020) by the Armed Forces Epidemiology and Public Health Center]

Objectives

Faced with the COVID-19 epidemic that occurred within the naval air group and the nuclear aircraft carrier Charles de Gaulle, the French Armed Forces Epidemiology and Public Health Center (CESPA) carried out an investigation (January - April 2020) whose objectives were: to identify the possible routes of introduction of the virus ; to describe the characteristics of the epidemic and to describe and model the dynamics of the epidemic's spread.

Methods

A telephone survey was conducted. The biological diagnoses were transmitted by the medical antennas. A time/place/population analysis was carried out, as well as the description of the clinical pictures with their exposure factors. The instantaneous reproduction rate Rt of the epidemic was modeled. A spatial analysis of the epidemic on board was carried out. Forty-three viral genomes were sequenced and compared to the reference bases.

Results

0f 1767 sailors, 1568 (89%) participated in the telephone survey and 1064 (67.9%) were confirmed cases. Four patient profiles have been described: asymptomatic (13.0%); non-specific symptomatic (8.1%); specific symptomatic (76.3%); severe cases (2.6%). In univariate and multivariate analysis, age, overweight and obesity were significantly associated with the risk of having a severe form. Smoking was a protective factor. The evolution kinetics of Rt was in favor of an introduction of the virus at the end of February with a reintroduction during the stopover in Brest. Analysis of viral genomes ruled out introduction and spread of a single strain.

Conclusion

Despite the control measures taken, an epidemic occurred. The often pauci-symptomatic clinical pictures resulted in a delay in identification. CESPA was able to carry out this epidemiological investigation within a highly constrained timeframe, showing all the interest of its integrated public health model.

Effects of healthcare system transformations spurred by the COVID-19 pandemic on management of stroke and STEMI: a registry-based cohort study in France

OBJECTIVE

To assess the impact of changes in use of care and implementation of hospital reorganisations spurred by the COVID-19 pandemic (first wave) on the acute management times of patients who had a stroke and ST-segment elevation myocardial infarction (STEMI).

DESIGN

Two cohorts of patients who had an STEMI and stroke in the Aquitaine Cardio-Neuro-Vascular (CNV) registry.

SETTING

6 emergency medical services, 30 emergency units (EUs), 14 hospitalisation units and 11 cathlabs in the Aquitaine region.

PARTICIPANTS

This study involved 9218 patients (6436 patients who had a stroke and 2782 patients who had an STEMI) in the CNV Registry from January 2019 to August 2020.

METHOD

Hospital reorganisations, retrieved in a scoping review, were collected from heads of hospital departments. Other data were from the CNV Registry. Associations between reorganisations, use of care and care management times were analysed using multivariate linear regression mixed models. Interaction terms between use-of-care variables and period (pre-wave, per-wave and post-wave) were introduced.

MAIN OUTCOME MEASURES

STEMI cohort, first medical contact-to-procedure time; stroke cohort, EU admission-to-imaging time.

RESULTS

Per-wave period management times deteriorated for stroke but were maintained for STEMI. Per-wave changes in use of care did not affect STEMI management. No association was found between reorganisations and stroke management times. In the STEMI cohort, the implementation of systematic testing at admission was associated with a 41% increase in care management time (exp=1.409, 95% CI 1.075 to 1.848, p=0.013). Implementation of plan blanc, which concentrated resources in emergency activities, was associated with a 19% decrease in management time (exp=0.801, 95% CI 0.639 to 1.023, p=0.077).

CONCLUSIONS

The pandemic did not markedly alter the functioning of the emergency network. Although stroke patient management deteriorated, the resilience of the STEMI pathway was linked to its stronger structuring. Transversal reorganisations, aiming at concentrating resources on emergency care, contributed to maintenance of the quality of care.

TRIAL REGISTRATION NUMBER

NCT04979208.

Methods Used in the Spatial and Spatiotemporal Analysis of COVID-19 Epidemiology: A Systematic Review

The spread of the COVID-19 pandemic was spatially heterogeneous around the world; the transmission of the disease is driven by complex spatial and temporal variations in socioenvironmental factors. Spatial tools are useful in supporting COVID-19 control programs. A substantive review of the merits of the methodological approaches used to understand the spatial epidemiology of the disease is hardly undertaken. In this study, we reviewed the methodological approaches used to identify the spatial and spatiotemporal variations of COVID-19 and the socioeconomic, demographic and climatic drivers of such variations. We conducted a systematic literature search of spatial studies of COVID-19 published in English from Embase, Scopus, Medline, and Web of Science databases from 1 January 2019 to 7 September 2021. Methodological quality assessments were also performed using the Joanna Briggs Institute (JBI) risk of bias tool. A total of 154 studies met the inclusion criteria that used frequentist (85%) and Bayesian (15%) modelling approaches to identify spatial clusters and the associated risk factors. Bayesian models in the studies incorporated various spatial, temporal and spatiotemporal effects into the modelling schemes. This review highlighted the need for more local-level advanced Bayesian spatiotemporal modelling through the multi-level framework for COVID-19 prevention and control strategies.

Use of Recently Vaccinated Individuals to Detect Bias in Test-Negative Case-Control Studies of COVID-19 Vaccine Effectiveness

Postauthorization observational studies play a key role in understanding COVID-19 vaccine effectiveness following the demonstration of efficacy in clinical trials. Although bias due to confounding, selection bias, and misclassification can be mitigated through careful study design, unmeasured confounding is likely to remain in these observational studies. Phase III trials of COVID-19 vaccines have shown that protection from vaccination does not occur immediately, meaning that COVID-19 risk should be similar in recently vaccinated and unvaccinated individuals, in the absence of confounding or other bias. Several studies have used the estimated effectiveness among recently vaccinated individuals as a negative control exposure to detect bias in vaccine effectiveness estimates. In this paper, we introduce a theoretical framework to describe the interpretation of such a bias indicator in test-negative studies, and outline strong assumptions that would allow vaccine effectiveness among recently vaccinated individuals to serve as a negative control exposure.

Clustering and mapping the first COVID-19 outbreak in France

BACKGROUND

With more than 160 000 confirmed COVID-19 cases and about 30 000 deceased people at the end of June 2020, France was one of the countries most affected by the coronavirus crisis worldwide. We aim to assess the efficiency of global lockdown policy in limiting spatial contamination through an in-depth reanalysis of spatial statistics in France during the first lockdown and immediate post-lockdown phases.

METHODS

To reach that goal, we use an integrated approach at the crossroads of geography, spatial epidemiology, and public health science. To eliminate any ambiguity relevant to the scope of the study, attention focused at first on data quality assessment. The data used originate from official databases (Santé Publique France) and the analysis is performed at a departmental level. We then developed spatial autocorrelation analysis, thematic mapping, hot spot analysis, and multivariate clustering.

RESULTS

We observe the extreme heterogeneity of local situations and demonstrate that clustering and intensity are decorrelated indicators. Thematic mapping allows us to identify five "ghost" clusters, whereas hot spot analysis detects two positive and two negative clusters. Our re-evaluation also highlights that spatial dissemination follows a twofold logic, zonal contiguity and linear development, thus determining a "metastatic" propagation pattern.

CONCLUSIONS

One of the most problematic issues about COVID-19 management by the authorities is the limited capacity to identify hot spots. Clustering of epidemic events is often biased because of inappropriate data quality assessment and algorithms eliminating statistical-spatial outliers. Enhanced detection techniques allow for a better identification of hot and cold spots, which may lead to more effective political decisions during epidemic outbreaks.

Characteristics of X-ray pattern of lung lesion in COVID-19 in adult patients with cystic fibrosis

Background. Patients with cystic fibrosis (CF) fall into the risk group of breathing passages infection as a result of clinical features of the disease. During the period of COVID-19 pandemic,the necessity of understanding how infection affects the course of the main disease has appeared, taking into account that viability of patients is essentially determined by the degree of lung lesion. Early diagnostics and complex therapy of coronavirus infection increase the lifespan of CF patients and improve quality of life. X-ray examinations play the leading role in solving this problem. Purpose – to establish risk factors of the main pathological process aggravation by determining diagnostic significance of roentgen sings of lung lesion in COVID-19 in CF adult patients. Materials and methods. Theanalysis of radiography and computed tomography results of 11 adult patients with CF of moderate and severe degree who were also diagnosed with coronavirus infection. Results. The main X-ray symptoms in observed patients with CF with confirmed diagnosis of coronavirus infection was pneumonic infiltration of different degrees in the setting of diffuse changes of lung pattern and features of pulmonary emphysema. Besides symptoms of the main disease, computed tomography allowed us to find the signs, which we consider to be the signs of pneumonia caused by COVID-19 infection – induration of lung tissue in the form of ground-glass opacity, presence of ground-glass areas of different shapes with reticular changes and consolidation of lung tissue, bilateral localization of pathological changes, predominantly in basal and subpleural areas. Conclusions. Lung lesion conditioned by COVID-19 in radiography of CF patients may be disguised by the features of the main disease manifestations. Therefore, any X-ray evidence of inflammatory lung changes in CF patients during the epidemic period must be regarded as COVID-19 suspected, and polymerase chain reaction and computed tomography must be performed.

Characteristics of COVID-19 Inpatients in Rehabilitation Units during the First Pandemic Wave: A Cohort Study from a Large Hospital in Champagne Region

Background: Data describing patients hospitalized in medical rehabilitation wards after the acute phase of COVID-19 could help to better understand the rehabilitation needs in the current pandemic situation. Methods: Cohort including all patients with COVID-19 hospitalized in a single, large university hospital in Northeast France from 25 February to 30 April 2020. Results: 479 patients were admitted with COVID-19 during the study period, of whom 128 died (26.7%). Among the 351 survivors, 111 were referred to rehabilitation units, including 63 (17.9%) referred to physical and rehabilitation medicine (PRM) units. The median age of patients referred to rehabilitation units was 72 years. Patients who had been in intensive care, or who had had a long hospital stay, required referral to PRM units. Two biomarkers were associated with referral to rehabilitation units, namely, elevated troponin (p = 0.03) and impaired renal function (p = 0.03). Age was associated with referral to PRM units (p = 0.001). Conclusions: Almost one-third of COVID-19 patients required post-acute care, but only one-fifth had access to PRM units. The optimal strategy for post-acute management of COVID-19 patients remains to be determined. The need for rehabilitation wards during a pandemic is a primary concern in enabling the long-term functioning of infected patients.

Geographical distribution of cystic fibrosis carriers as population genetic determinant of COVID-19 spread and fatality in 37 countries

COVID-19 has shown a relevant heterogeneity in spread and fatality among countries together with a significant variability in its clinical presentation, indicating that host genetic factors may influence COVID-19 pathogenicity. Indeed, subjects carrying single pathogenic variants of the Cystic Fibrosis (CF) Transmembrane Conductance Regulator (CFTR) gene – i.e. CF carriers – are more susceptible to respiratory tract infections and are more likely to undergo severe COVID-19 with higher risk of 14-day mortality.

Given that CF carrier prevalence varies among ethnicities and nations, an ecological study in 37 countries was conducted, in order to determine to what extent the diverse CF carrier geographical distribution may have affected COVID-19 spread and fatality during the first pandemic wave.

The CF prevalence in countries, as indicator of the geographical distribution of CF carriers, significantly correlated in a direct manner with both COVID-19 prevalence and its Case Fatality Rate (CFR). In a regression study weighted for the number of tests performed, COVID-19 prevalence positively correlated with CF prevalence, while CFR correlated with population percentage older than 65-year, cancer and CF prevalence. Multivariate regression model also confirmed COVID-19 CFR to be associated with CF prevalence, after adjusting for elderly, cancer prevalence, and weighting for the number of tests performed.

This study suggests a putative contribution of population genetics of CFTR in understanding the spatial distribution of COVID-19 spread and fatality.

Investigation of a COVID-19 outbreak on the Charles de Gaulle aircraft carrier, March to April 2020: a retrospective cohort study

Background

SARS-CoV-2 emergence was a threat for armed forces. A COVID-19 outbreak occurred on the French aircraft carrier Charles de Gaulle from mid-March to mid-April 2020.

Aim

To understand how the virus was introduced, circulated then stopped circulation, risk factors for infection and severity, and effectiveness of preventive measures.

Methods

We considered the entire crew as a cohort and collected personal, clinical, biological, and epidemiological data. We performed viral genome sequencing and searched for SARS-CoV-2 in the environment.

Results

The attack rate was 65% (1,148/1,767); 1,568 (89%) were included. The male:female ratio was 6.9, and median age was 29 years (IQR: 24–36). We examined four clinical profiles: asymptomatic (13.0%), non-specific symptomatic (8.1%), specific symptomatic (76.3%), and severe (i.e. requiring oxygen therapy, 2.6%). Active smoking was not associated with severe COVID-19; age and obesity were risk factors. The instantaneous reproduction rate (R_t) and viral sequencing suggested several introductions of the virus with 4 of 5 introduced strains from within France, with an acceleration of R_t when lifting preventive measures. Physical distancing prevented infection (adjusted OR: 0.55; 95% CI: 0.40–0.76). Transmission may have stopped when the proportion of infected personnel was large enough to prevent circulation (65%; 95% CI: 62–68).

Conclusion

Non-specific clinical pictures of COVID-19 delayed detection of the outbreak. The lack of an isolation ward made it difficult to manage transmission; the outbreak spread until a protective threshold was reached. Physical distancing was effective when applied. Early surveillance with adapted prevention measures should prevent such an outbreak.

Who Were Hospitalized Deceased Patients from COVID-19 During the First Year of Pandemic? Retrospective Analysis of 1104 Deceased Patients in South of France

Introduction

Following the first year of the COVID-19 pandemic, a complete analysis of the characteristics of the deceased hospitalized patients was performed, to identify factors related to premature mortality and to compare patient profiles according to the epidemic periods.

Methods

Retrospective analysis of 1104 deceased patients in two University Hospitals in South-eastern France, between March 1, 2020 and March 12, 2021 from Hospital’s electronic medical records was performed.

Results

Mean age was 80 years (± 11.1) and 10% of the deceased were younger than 65 years with specific comorbidities, e.g., genetic conditions, metastatic cancer, or massive obesity. Among the three clusters identified, two clusters (75% of deceased patients) include very elderly patients with numerous comorbidities, and differ by their proportion of dependent institutionalized patients. The third cluster is made up of younger patients with fewer but severe comorbidities. Deceased patients’ profiles varied according to the epidemic periods: during the first period (March–June 2020), more patients were institutionalized. The second period (September–December2020) coincided with a higher mortality rate.

Conclusions

This study confirmed that most patients hospitalized and dying from COVID-19 were frail, i.e., elderly and/or highly comorbid and that the small proportion of young patients had severe comorbidities.

Supplementary Information

The online version contains supplementary material available at 10.1007/s44197-022-00039-3.

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.

Hospital acquired COVID-19 infections amongst patients before the rollout of COVID-19 vaccinations, a scoping review

Background

Hospital settings are at increased risk of spreading Coronavirus Disease 2019 (COVID-19) infections, hence non-pharmaceutical prevention interventions (NPPIs) and prioritized vaccination of healthcare workers and resident patients are critical. The status of COVID-19 hospital acquired infections (HAIs) in low-income settings is unclear. We aimed to identify and summarize the existing evidence on COVID-19 HAIs amongst patients, prior to the rollout of vaccines in countries worldwide.

Methods

We conducted a scoping review of English peer-reviewed literature in PubMed, Web of Science and Scopus using a combination of selected search terms. Full texts articles presenting results on COVID-19 HAIs in hospitalised patients before the rollout of vaccines in countries worldwide were eligible. Data extracted from eligible articles included estimates of COVID-19 HAIs, country, and type of hospital setting, and was summarized narratively. Quality assessment of included articles was not possible.

Results

Literature searches generated a total of 5920 articles, and 45 were eligible for analysis. Eligible articles were from Europe, North America, Asia, and Brazil and none were from low-income countries. The proportion of COVID-19 HAIs ranged from 0% when strict NPPIs were applied, to 65% otherwise. The estimates of COVID-19 HAIs did not differ by country but were lower in studies conducted after implementation of NPPIs and in specialized hospital settings for operative surgery. Studies conducted before the implementation of NPPIs or in long-term care and psychiatric wards often reported high estimates of HAI. Although there was no clear trend in general wards, those situated in academic hospitals managed to reduce HAI rates under strict NPPI protocols. Operative surgery settings, unlike psychiatric settings, effectively prevented COVID-19 HAI using tailored NPPIs.

Conclusion

The available evidence shows a high risk of COVID-19 HAIs, the feasibility of preventing HAIs in different healthcare settings and the importance of appropriately tailored NPPIs. There were no data from low-income settings, therefore, it is unclear whether the reported NPPI approaches could be equally effective elsewhere. We recommend routine monitoring of COVID-19 HAIs in countries with low vaccination coverage, to identify and close gaps in NPPIs and understand gains made from vaccinating healthcare workers and hospitalized patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07128-5.

Spatial analysis of COVID-19 hospitalised cases in an entire city: The risk of studying only lattice data

We live in a global pandemic caused by the COVID-19 disease where severe social distancing measures are necessary. Some of these measures have been taken into account by the administrative boundaries within cities (neighborhoods, postal districts, etc.). However, considering only administrative boundaries in decision making can prove imprecise, and could have consequences when it comes to taking effective measures. To solve the described problems, we present an epidemiological study that proposes using spatial point patterns to delimit spatial units of analysis based on the highest local incidence of hospitalisations instead of administrative limits during the first COVID-19 wave. For this purpose, the 579 addresses of the cases hospitalised between March 3 and April 6, 2020, in Albacete (Spain), and the addresses of the random sample of 383 controls from the Inhabitants Register of the city of Albacete, were georeferenced. The risk ratio in those hospitalised for COVID-19 was compatible with the constant risk ratio in Albacete (p = 0.49), but areas with a significantly higher risk were found and coincided with those with greater economic inequality (Gini Index). Moreover, two districts had areas with a significantly high incidence that were masked by others with a significantly low incidence. In conclusion, taking measures conditioned exclusively by administrative limits in a pandemic can cause problems caused by managing entire districts with lax measures despite having interior areas with high significant incidences. In a pandemic context, georeferencing disease cases in real time and spatially comparing them to updated random population controls to automatically and accurately detect areas with significant incidences are suggested. This would facilitate decision making, which must be fast and accurate in these situations.

Heterogeneity of the COVID-19 Pandemic in the United States of America: A Geo-Epidemiological Perspective

The spread of the COVID-19 pandemic has shown great heterogeneity between regions of countries, e. g., in the United States of America (USA). With the growing of the worldwide COVID-19 pandemic, there is a need to better highlight the variability in the trajectory of this disease in different worldwide geographic areas. Indeed, the epidemic trends across areas can display completely different evolution at a given time. Geo-epidemiological analyses using data, that are publicly available, could be a major topic to help governments and public administrations to implement health policies. Geo-epidemiological analyses could provide a basis for the implementation of relevant public health policies. With the COVID-19 pandemic, geo-epidemiological analyses can be readily utilized by policy interventions and USA public health authorities to highlight geographic areas of particular concern and enhance the allocation of resources.

Identifying extreme COVID-19 mortality risks in English small areas: a disease cluster approach

The COVID-19 pandemic is having a huge impact worldwide and has highlighted the extent of health inequalities between countries but also in small areas within a country. Identifying areas with high mortality is important both of public health mitigation in COVID-19 outbreaks, and of longer term efforts to tackle social inequalities in health. In this paper we consider different statistical models and an extension of a recent method to analyze COVID-19 related mortality in English small areas during the first wave of the epidemic in the first half of 2020. We seek to identify hotspots, and where they are most geographically concentrated, taking account of observed area factors as well as spatial correlation and clustering in regression residuals, while also allowing for spatial discontinuities. Results show an excess of COVID-19 mortality cases in small areas surrounding London and in other small areas in North-East and and North-West of England. Models alleviating spatial confounding show ethnic isolation, air quality and area morbidity covariates having a significant and broadly similar impact on COVID-19 mortality, whereas nursing home location seems to be slightly less important.

Identifying extreme COVID-19 mortality risks in English small areas: a disease cluster approach

The COVID-19 pandemic is having a huge impact worldwide and has highlighted the extent of health inequalities between countries but also in small areas within a country. Identifying areas with high mortality is important both of public health mitigation in COVID-19 outbreaks, and of longer term efforts to tackle social inequalities in health. In this paper we consider different statistical models and an extension of a recent method to analyze COVID-19 related mortality in English small areas during the first wave of the epidemic in the first half of 2020. We seek to identify hotspots, and where they are most geographically concentrated, taking account of observed area factors as well as spatial correlation and clustering in regression residuals, while also allowing for spatial discontinuities. Results show an excess of COVID-19 mortality cases in small areas surrounding London and in other small areas in North-East and and North-West of England. Models alleviating spatial confounding show ethnic isolation, air quality and area morbidity covariates having a significant and broadly similar impact on COVID-19 mortality, whereas nursing home location seems to be slightly less important.

Georeferencing of COVID-19 Positive Nasopharyngeal Swabs to Support Emergency Management in an Area of Northern Italy

Spatial distribution heterogeneity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been observed in several countries. While previous studies have covered vast geographic areas, detailed analyses on smaller territories are not available to date. The aim of our study was to understand the spatial spread of SARS-CoV-2 in a province of Northern Italy through the analysis of positive nasopharyngeal (NP) swabs. The study was conducted on subjects who lived in the province of Alessandria with at least one positive NP swab between 2 March and 22 December 2020. To investigate if clustering occurred, the proportion of SARS-CoV-2 positive subjects over the total number of residents in each small administrative subregion was calculated and then mapped. A total of 17,260 subjects with at least one positive NP swab were included; the median age was 54 years (Interquartile range 38–72) and 54.9% (n = 9478) of our study population were female. Among the 192 towns scanned, 26 showed a prevalence between 5% and 7.5%, one between 7.5% and 10% and two with more than 10% positive swabs. The territories with a higher prevalence of positive subjects were located in areas with at least one nursing home and potential clusters were observed within these structures. The maps produced may be considered a useful and important monitoring system to identify areas with a significant and relevant diffusion of SARS-CoV-2.

Estimating the impact of influenza on the epidemiological dynamics of SARS-CoV-2

As in past pandemics, co-circulating pathogens may play a role in the epidemiology of coronavirus disease 2019 (COVID-19), caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In particular, experimental evidence indicates that influenza infection can up-regulate the expression of ACE2-the receptor of SARS-CoV-2 in human cells-and facilitate SARS-CoV-2 infection. Here we hypothesized that influenza impacted the epidemiology of SARS-CoV-2 during the early 2020 epidemic of COVID-19 in Europe. To test this hypothesis, we developed a population-based model of SARS-CoV-2 transmission and of COVID-19 mortality, which simultaneously incorporated the impact of non-pharmaceutical control measures and of influenza on the epidemiological dynamics of SARS-CoV-2. Using statistical inference methods based on iterated filtering, we confronted this model with mortality incidence data in four European countries (Belgium, Italy, Norway, and Spain) to systematically test a range of assumptions about the impact of influenza. We found consistent evidence for a 1.8-3.4-fold (uncertainty range across countries: 1.1 to 5.0) average population-level increase in SARS-CoV-2 transmission associated with influenza during the period of co-circulation. These estimates remained robust to a variety of alternative assumptions regarding the epidemiological traits of SARS-CoV-2 and the modeled impact of control measures. Although further confirmatory evidence is required, our results suggest that influenza could facilitate the spread and hamper effective control of SARS-CoV-2. More generally, they highlight the possible role of co-circulating pathogens in the epidemiology of COVID-19.

Spatial determinants of excess all-cause mortality during the first wave of the COVID-19 epidemic in France

BACKGROUND

The first wave of the COVID-19 pandemic in France was associated with high excess mortality, and anecdotal evidence pointed to differing excess mortality patterns depending on social and environmental determinants. In this study we aimed to investigate the spatial distribution of excess mortality during the first wave of the COVID-19 pandemic in France and relate it at the subnational level to contextual determinants from various dimensions (socioeconomic, population density, overall health status, healthcare access etc.). We also explored whether the determinants identified at the national level varied depending on geographical location.

METHODS

We used available national data on deaths in France to calculate excess mortality by department for three age groups: 0-49, 50-74 and > 74 yrs. between March 1st and April 27th, 2020. We selected 15 variables at the department level that represent four dimensions that may be related to overall mortality at the ecological level, two representing population-level vulnerabilities (morbidity, social deprivation) and two representing environmental-level vulnerabilities (primary healthcare supply, urbanization). We modelled excess mortality by age group for our contextual variables at the department level. We conducted both a global (i.e., country-wide) analysis and a multiscale geographically weighted regression (MGWR) model to account for the spatial variations in excess mortality.

RESULTS

In both age groups, excess all-cause mortality was significantly higher in departments where urbanization was higher (50-74 yrs.: β = 15.33, p < 0.001; > 74 yrs.: β = 18.24, p < 0.001) and the supply of primary healthcare providers lower (50-74 yrs.: β = - 8.10, p < 0.001; > 74 yrs.: β = - 8.27, p < 0.001). In the 50-74 yrs. age group, excess mortality was negatively associated with the supply of pharmacists (β = - 3.70, p < 0.02) and positively associated with work-related mobility (β = 4.62, p < 0.003); in the > 74 yrs. age group our measures of deprivation (β = 15.46, p < 0.05) and morbidity (β = 0.79, p < 0.008) were associated with excess mortality. Associations between excess mortality and contextual variables varied significantly across departments for both age groups.

CONCLUSIONS

Public health strategies aiming at mitigating the effects of future epidemics should consider all dimensions involved to develop efficient and locally tailored policies within the context of an evolving, socially and spatially complex situation.

Estimation of Daily Reproduction Numbers during the COVID-19 Outbreak

(1) Background: The estimation of daily reproduction numbers throughout the contagiousness period is rarely considered, and only their sum R0 is calculated to quantify the contagiousness level of an infectious disease. (2) Methods: We provide the equation of the discrete dynamics of the epidemic’s growth and obtain an estimation of the daily reproduction numbers by using a deconvolution technique on a series of new COVID-19 cases. (3) Results: We provide both simulation results and estimations for several countries and waves of the COVID-19 outbreak. (4) Discussion: We discuss the role of noise on the stability of the epidemic’s dynamics. (5) Conclusions: We consider the possibility of improving the estimation of the distribution of daily reproduction numbers during the contagiousness period by taking into account the heterogeneity due to several host age classes.

Interplay between mobility, multi-seeding and lockdowns shapes COVID-19 local impact

Assessing the impact of mobility on epidemic spreading is of crucial importance for understanding the effect of policies like mass quarantines and selective re-openings. While many factors affect disease incidence at a local level, making it more or less homogeneous with respect to other areas, the importance of multi-seeding has often been overlooked. Multi-seeding occurs when several independent (non-clustered) infected individuals arrive at a susceptible population. This can lead to independent outbreaks that spark from distinct areas of the local contact (social) network. Such mechanism has the potential to boost incidence, making control efforts and contact tracing less effective. Here, through a modeling approach we show that the effect produced by the number of initial infections is non-linear on the incidence peak and peak time. When case importations are carried by mobility from an already infected area, this effect is further enhanced by the local demography and underlying mixing patterns: the impact of every seed is larger in smaller populations. Finally, both in the model simulations and the analysis, we show that a multi-seeding effect combined with mobility restrictions can explain the observed spatial heterogeneities in the first wave of COVID-19 incidence and mortality in five European countries. Our results allow us for identifying what we have called epidemic epicenter: an area that shapes incidence and mortality peaks in the entire country. The present work further clarifies the nonlinear effects that mobility can have on the evolution of an epidemic and highlight their relevance for epidemic control.