Excess cases of influenza-like illnesses synchronous with coronavirus disease (COVID-19) epidemic, France, March 2020

Monitoring COVID-19 in Belgian general practice: A tool for syndromic surveillance based on electronic health records

BACKGROUND

COVID-19 may initially manifest as flu-like symptoms. As such, general practitioners (GPs) will likely to play an important role in monitoring the pandemic through syndromic surveillance.

OBJECTIVES

To present a COVID-19 syndromic surveillance tool in Belgian general practices.

METHODS

We performed a nationwide observational prospective study in Belgian general practices. The surveillance tool extracted the daily entries of diagnostic codes for COVID-19 and associated conditions (suspected or confirmed COVID-19, acute respiratory infection and influenza-like illness) from electronic medical records. We calculated the 7-day rolling average for these diagnoses and compared them with data from two other Belgian population-based sources (laboratory-confirmed new COVID-19 cases and hospital admissions for COVID-19), using time series analysis. We also collected data from users and stakeholders about the syndromic surveillance tool and performed a thematic analysis.

RESULTS

4773 out of 11,935 practising GPs in Belgium participated in the study. The curve of contacts for suspected COVID-19 followed a similar trend compared with the curves of the official data sources: laboratory-confirmed COVID-19 cases and hospital admissions but with a 10-day delay for the latter. Data were quickly available and useful for decision making, but some technical and methodological components can be improved, such as a greater standardisation between EMR software developers.

CONCLUSION

The syndromic surveillance tool for COVID-19 in primary care provides rapidly available data useful in all phases of the COVID-19 pandemic to support data-driven decision-making. Potential enhancements were identified for a prospective surveillance tool.

Primary care indicators for disease burden, monitoring and surveillance of COVID-19 in 31 European countries: Eurodata Study

BACKGROUND

During the COVID-19 pandemic, the majority of patients received ambulatory treatment, highlighting the importance of primary health care (PHC). However, there is limited knowledge regarding PHC workload in Europe during this period. The utilization of COVID-19 PHC indicators could facilitate the efficient monitoring and coordination of the pandemic response. The objective of this study is to describe PHC indicators for disease surveillance and monitoring of COVID-19's impact in Europe.

METHODS

Descriptive, cross-sectional study employing data obtained through a semi-structured ad hoc questionnaire, which was collectively agreed upon by all participants. The study encompasses PHC settings in 31 European countries from March 2020 to August 2021. Key-informants from each country answered the questionnaire. Main outcome: the identification of any indicator used to describe PHC COVID-19 activity.

RESULTS

Out of the 31 countries surveyed, data on PHC information were obtained from 14. The principal indicators were: total number of cases within PHC (Belarus, Cyprus, Italy, Romania and Spain), number of follow-up cases (Croatia, Cyprus, Finland, Spain and Turkey), GP's COVID-19 tests referrals (Poland), proportion of COVID-19 cases among respiratory illnesses consultations (Norway and France), sick leaves issued by GPs (Romania and Spain) and examination and complementary tests (Cyprus). All COVID-19 cases were attended in PHC in Belarus and Italy.

CONCLUSIONS

The COVID-19 pandemic exposes a crucial deficiency in preparedness for infectious diseases in European health systems highlighting the inconsistent recording of indicators within PHC organizations. PHC standardized indicators and public data accessibility are urgently needed, conforming the foundation for an effective European-level health services response framework against future pandemics.

Coupling between infectious diseases leads to synchronization of their dynamics

Interactions between different diseases may change their dynamics. Thus, these interactions represent a source of uncertainty in the modeling of empirical data when the symptoms of both infections are hard to distinguish. We recall previously proposed models of interacting infections, generalizing them to non-symmetric scenarios, showing that both cooperative and competitive interactions lead to synchronization of the maximum fraction of infected individuals in their dynamics. We exemplify this framework with a model coupling the dynamics of COVID-19 and seasonal influenza, simulating cooperation, competition, and asymmetric interactions. We find that the coupling synchronizes both infections, with a stronger influence on the dynamics of influenza.

Human metapneumovirus in hospitalized children with acute respiratory tract infections in Beijing, China

BACKGROUND

This study aims to described the epidemiology and genotypic diversity of Human metapneumovirus (HMPV) and the impact of SARS-CoV-2 on the prevalence of HMPV in hospitalized children with Acute respiratory tract infections (ARTIs) in Beijing, China.

METHODS

From April 2018 to March 2019 and from September 2020 to August 2021, nasopharyngeal aspirates (NPAs) from hospitalized children with ARTIs in Beijing were collected and subjected to real-time polymerase chain reaction tests for HMPV. Then genotyping, detection of 15 common respiratory viruses and clinical characteristics were analyzed on HMPV positive samples.

RESULTS

7.9% (124/1572) enrolled pediatric patients were identified as having HMPV infection, and the majority of children under the age of 5 (78.2%, 92/124), From April 2018 to March 2019. The detection rate of HMPV in spring and winter is significantly higher than that in summer and autumn. The co-infection rate were 37.1% (46/124), the most common co-infected virus were parainfluenza virus type 3 (HPIV-3). The main diagnosis of HMPV infection was pneumonia (92.7%,115/124), most patient have cough and fever. Of 78 HMPV-positive specimens, A2b (82.1%,64/78) were the main epidemic subtypes. Hospitalized children with HMPV genotype A infection had a higher viral load compared to genotype B. During the COVID-19 outbreak, Among 232 samples, only 4 cases were HMPV-positive. After statistical test, the detection rate of HMPV during the COVID-19 pandemic has decreased significantly compared with that before the epidemic (p = 0.001).

CONCLUSIONS

HMPV is an important cause of ARTIs in children under 5 years old. The epidemic peak is generally in winter and spring, and the A2b subtype is the most common. However, under the prevention and control of the COVID-19 pandemic, the HMPV infection of hospitalized children with ARTIs has decreased significantly.

Lockdown measures during the COVID-19 pandemic strongly impacted the circulation of respiratory pathogens in Southern China

A range of public health measures have been implemented to suppress local transmission of coronavirus disease 2019 (COVID-19) in Shenzhen. We examined the effect of these measures on the prevalence of respiratory pathogens in children. Clinical and respiratory pathogen data were collected for routine care from hospitalized children with acute respiratory infections in Shenzhen Children's Hospital from July 2018 to January 2022. Nasopharyngeal swabs were collected and respiratory pathogens were detected using standardized clinical diagnostics as part of routine care. Data were analyzed to describe the effects of COVID-19 prevention procedures on other common pathogens. A total of 56,325 children under 14 years of age were hospitalized with an acute respiratory infection during the study period, 33,909 were tested from July 2018 to January 2020 (pre-lockdown), 1168 from February 2020 to May 2020 (lockdown) and 21,248 from July 2020 to January 2022 (post-lockdown). We observed a 37.3% decline of routine care in respiratory infection associated hospital admission in the 19 months' post-lockdown vs. the 19 months' pre-lockdown. There were 99.4%, 16.0% and 1.26% reductions measured for Mycoplasma pneumoniae, influenza virus A and adenovirus, respectively. However, a 118.7% and 75.8% rise was found for respiratory syncytial virus (RSV) and human para-influenza virus (HPIV) during the 19 months' post-lockdown in comparison to the pre-pandemic period. The detection of RSV especially increased in toddlers after the lockdown. Lockdown measures during the COVID-19 pandemic led to a significant reduction of Mycoplasma pneumoniae, influenza virus A and adenovirus infection. In contrast, RSV and HPIV infection increased.

Global influenza surveillance systems to detect the spread of influenza-negative influenza-like illness during the COVID-19 pandemic: Time series outlier analyses from 2015-2020

BACKGROUND

Surveillance systems are important in detecting changes in disease patterns and can act as early warning systems for emerging disease outbreaks. We hypothesized that analysis of data from existing global influenza surveillance networks early in the COVID-19 pandemic could identify outliers in influenza-negative influenza-like illness (ILI). We used data-driven methods to detect outliers in ILI that preceded the first reported peaks of COVID-19.

METHODS AND FINDINGS

We used data from the World Health Organization's Global Influenza Surveillance and Response System to evaluate time series outliers in influenza-negative ILI. Using automated autoregressive integrated moving average (ARIMA) time series outlier detection models and baseline influenza-negative ILI training data from 2015-2019, we analyzed 8,792 country-weeks across 28 countries to identify the first week in 2020 with a positive outlier in influenza-negative ILI. We present the difference in weeks between identified outliers and the first reported COVID-19 peaks in these 28 countries with high levels of data completeness for influenza surveillance data and the highest number of reported COVID-19 cases globally in 2020. To account for missing data, we also performed a sensitivity analysis using linear interpolation for missing observations of influenza-negative ILI. In 16 of the 28 countries (57%) included in this study, we identified positive outliers in cases of influenza-negative ILI that predated the first reported COVID-19 peak in each country; the average lag between the first positive ILI outlier and the reported COVID-19 peak was 13.3 weeks (standard deviation 6.8). In our primary analysis, the earliest outliers occurred during the week of January 13, 2020, in Peru, the Philippines, Poland, and Spain. Using linear interpolation for missing data, the earliest outliers were detected during the weeks beginning December 30, 2019, and January 20, 2020, in Poland and Peru, respectively. This contrasts with the reported COVID-19 peaks, which occurred on April 6 in Poland and June 1 in Peru. In many low- and middle-income countries in particular, the lag between detected outliers and COVID-19 peaks exceeded 12 weeks. These outliers may represent undetected spread of SARS-CoV-2, although a limitation of this study is that we could not evaluate SARS-CoV-2 positivity.

CONCLUSIONS

Using an automated system of influenza-negative ILI outlier monitoring may have informed countries of the spread of COVID-19 more than 13 weeks before the first reported COVID-19 peaks. This proof-of-concept paper suggests that a system of influenza-negative ILI outlier monitoring could have informed national and global responses to SARS-CoV-2 during the rapid spread of this novel pathogen in early 2020.

The impact of SARS-CoV-2 on respiratory syndromic and sentinel surveillance in Israel, 2020: a new perspective on established systems

Background

The COVID-19 pandemic presented new challenges for the existing respiratory surveillance systems, and adaptations were implemented. Systematic assessment of the syndromic and sentinel surveillance platforms during the pandemic is essential for understanding the value of each platform in the context of an emerging pathogen with rapid global spread.

Aim

We aimed to evaluate systematically the performance of various respiratory syndromic surveillance platforms and the sentinel surveillance system in Israel from 1 January to 31 December 2020.

Methods

We compared the 2020 syndromic surveillance trends to those of the previous 3 years, using Poisson regression adjusted for overdispersion. To assess the performance of the sentinel clinic system as compared with the national SARS-CoV-2 repository, a cubic spline with 7 knots and 95% confidence intervals were applied to the sentinel network's weekly percentage of positive SARS-CoV-2 cases.

Results

Syndromic surveillance trends changed substantially during 2020, with a statistically significant reduction in the rates of visits to physicians and emergency departments to below previous years' levels. Morbidity patterns of the syndromic surveillance platforms were inconsistent with the progress of the pandemic, while the sentinel surveillance platform was found to reflect the national circulation of SARS-CoV-2 in the population.

Conclusion

Our findings reveal the robustness of the sentinel clinics platform for the surveillance of the main respiratory viruses during the pandemic and possibly beyond. The robustness of the sentinel clinics platform during 2020 supports its use in locations with insufficient resources for widespread testing of respiratory viruses.

Non-Pharmaceutical Interventions Implemented to Control the COVID-19 Were Associated With Reduction of Influenza Incidence

Background

Non-pharmaceutical interventions were implemented in most countries to reduce the transmission of COVID-19. We aimed to describe the incidence of influenza in four countries in the 2019–2020 season and examined the effect of these non-pharmaceutical interventions on the incidence of influenza.

Methods

We used the network surveillance data from 2015 to 2020 to estimate the percentage increase in influenza cases to explore the effect of non-pharmaceutical interventions implemented to control the COVID-19 on the incidence of influenza in China, the United States, Japan, and Singapore.

Results

We found that the incidence of influenza has been almost zero and reached a persistent near-zero level for a continuous period of six months since epidemiologic week 14 of 2020 in the four countries. Influenza incidence decreased by 77.71% and 60.50% in the early days of COVID-19 in the 2019–2020 season compared to the same period in preceding years in Japan and Singapore, respectively. Furthermore, influenza incidence decreased by 60.50–99.48% during the period of compulsory interventions in the 2019–2020 season compared to the same period in preceding years in the four countries.

Conclusion

These findings suggest that the application of non-pharmaceutical interventions, even everyday preventive action, was associated with a reduction of influenza incidence, which highlights that more traditional public health interventions need to be reasserted and universalized to reduce influenza incidence.

Using an Administrative and Clinical Database to Determine the Early Spread of COVID-19 at the US Department of Veterans Affairs during the Beginning of the 2019–2020 Flu Season: A Retrospective Longitudinal Study

Background. Previous studies examining the early spread of COVID-19 have used influenza-like illnesses (ILIs) to determine the early spread of COVID-19. We used COVID-19 case definition to identify COVID-like symptoms (CLS) independently of other influenza-like illnesses (ILIs). Methods. Using data from Emergency Department (ED) visits at VA Medical Centers in CA, TX, and FL, we compared weekly rates of CLS, ILIs, and non-influenza ILIs encounters during five consecutive flu seasons (2015–2020) and estimated the risk of developing each illness during the first 23 weeks of the 2019–2020 season compared to previous seasons. Results. Patients with CLS were significantly more likely to visit the ED during the first 23 weeks of the 2019–2020 compared to prior seasons, while ED visits for influenza and non-influenza ILIs did not differ substantially. Adjusted CLS risk was significantly lower for all seasons relative to the 2019–2020 season: RR15–16 = 0.72, 0.75, 0.72; RR16–17 = 0.81, 0.77, 0.79; RR17–18 = 0.80, 0.89, 0.83; RR18–19 = 0.82, 0.96, 0.81, in CA, TX, and FL, respectively. Conclusions. The observed increase in ED visits for CLS indicates the likely spread of COVID-19 in the US earlier than previously reported. VA data could potentially help identify emerging infectious diseases and supplement existing syndromic surveillance systems.

Antihypertensive medications and COVID-19 diagnosis and mortality: Population-based case-control analysis in the United Kingdom

AIMS

Antihypertensive drugs have been implicated in coronavirus disease 2019 (COVID-19) susceptibility and severity, but estimated associations may be susceptible to bias. We aimed to evaluate antihypertensive medications and COVID-19 diagnosis and mortality, accounting for healthcare-seeking behaviour.

METHODS

A population-based case-control study was conducted including 16 866 COVID-19 cases and 70 137 matched controls from the UK Clinical Practice Research Datalink. We evaluated all-cause mortality among COVID-19 cases. Exposures were angiotensin-converting enzyme inhibitors (ACEIs), angiotensin receptor blockers (ARBs), beta-blockers (B), calcium-channel blockers (C), thiazide diuretics (D) and other antihypertensive drugs (O). Analyses were adjusted for covariates and consultation frequency.

RESULTS

ACEIs were associated with lower odds of COVID-19 diagnosis (adjusted odds ratio [AOR] 0.82, 95% confidence interval [CI] 0.77-0.88) as were ARBs (AOR 0.87, 95% CI 0.80-0.95) with little attenuation from adjustment for consultation frequency. C and D were also associated with lower odds of COVID-19 diagnosis. Increased odds of COVID-19 for B (AOR 1.19, 95% CI 1.12-1.26) were attenuated after adjustment for consultation frequency (AOR 1.01, 95% CI 0.95-1.08). Patients treated with ACEIs or ARBs had similar odds of mortality (AOR 1.00, 95% CI 0.83-1.20) to patients treated with classes B, C, D or O or patients receiving no antihypertensive therapy (AOR 0.99, 95% CI 0.83-1.18).

CONCLUSIONS

There was no evidence that antihypertensive therapy is associated with increased risk of COVID-19 diagnosis or mortality; most classes of antihypertensive therapy showed negative associations with COVID-19 diagnosis.

History of COVID-19 Symptoms and Seroprevalence of SARS-CoV-2 Antibodies in HIV-Infected Patients in Northern France after the First Wave of the Pandemic

To assess the prevalence of COVID-19 in people living with HIV (PLWHIV), we performed an epidemiological survey from 1 April through 1 August 2020 in an HIV reference center in Northern France. PLWHIV completed a questionnaire about risk exposures and symptoms consistent with COVID-19 and performed a SARS-CoV-2 serology. Among the 600 PLWHIV included, 16 have been infected with SARS-CoV-2. Symptoms consistent with COVID-19 were frequent both in SARS-CoV-2 positive and negative patients (67% vs. 32%, p = 0.02). Among SARS-CoV-2 infected patients, one (6%) has been hospitalized and five (31%) have been asymptomatic. Close contact with a confirmed COVID-19 case was the only factor associated with COVID-19 acquisition (40% vs. 13%, p = 0.01). The prevalence of COVID-19 in PLWHIV was 2.5%, half of the overall population estimate after the first wave of the pandemic in France. In conclusion, proportion of asymptomatic COVID-19 was high in PLWHIV. The prevalence of COVID-19 in PLWHIV was two times lower than in the general population.

Common communicable diseases in the general population in France during the COVID-19 pandemic

In France, social distancing measures have been adopted to contain the spread of COVID-19, culminating in national Lockdowns. The use of hand washing, hydro-alcoholic rubs and mask-wearing also increased over time. As these measures are likely to impact the transmission of many communicable diseases, we studied the changes in common infectious diseases incidence in France during the first year of COVID-19 circulation. We examined the weekly incidence of acute gastroenteritis, chickenpox, acute respiratory infections and bronchiolitis reported in general practitioner networks since January 2016. We obtained search engine query volume for French terms related to these diseases and sales data for relevant drugs over the same period. A periodic regression model was fit to disease incidence, drug sales and search query volume before the COVID-19 period and extrapolated afterwards. We compared the expected values with observations made in 2020. During the first lockdown period, incidence dropped by 67% for gastroenteritis, by 79% for bronchiolitis, by 49% for acute respiratory infection and 90% for chickenpox compared to the past years. Reductions with respect to the expected incidence reflected the strength of implemented measures. Incidence in children was impacted the most. Reduction in primary care consultations dropped during a short period at the beginning of the first lockdown period but remained more than 95% of the expected value afterwards. In primary care, the large decrease in reported gastroenteritis, chickenpox or bronchiolitis observed during the period where many barrier measures were implemented imply that the circulation of common viruses was reduced and informs on the overall effect of these measures.

Comparison of 11 respiratory pathogens among hospitalized children before and during the COVID-19 epidemic in Shenzhen, China

Background

The effect of SARS-CoV-2 on existing respiratory pathogens in circulation remains uncertain. This study aimed to assess the impact of SARS-CoV-2 on the prevalence of respiratory pathogens among hospitalized children.

Methods

This study enrolled hospitalized children with acute respiratory infections in Shenzhen Children’s Hospital from September to December 2019 (before the COVID-19 epidemic) and those from September to December 2020 (during the COVID-19 epidemic). Nasopharyngeal swabs were collected, and respiratory pathogens were detected using multiplex PCR. The absolute case number and detection rates of 11 pathogens were collected and analyzed.

Results

A total of 5696 children with respiratory tract infection received multiplex PCR examination for respiratory pathogens: 2298 from September to December 2019 and 3398 from September to December 2020. At least one pathogen was detected in 1850 (80.5%) patients in 2019, and in 2380 (70.0%) patients in 2020; the detection rate in 2020 was significantly lower than that in 2019.The Influenza A (InfA) detection rate was 5.6% in 2019, but 0% in 2020. The detection rates of Mycoplasma pneumoniae, Human adenovirus, and Human rhinovirus also decreased from 20% (460), 8.9% (206), and 41.8% (961) in 2019 to 1.0% (37), 2.1% (77), and 25.6% (873) in 2020, respectively. In contrast, the detection rates of Human respiratory syncytial virus, Human parainfluenza virus, and Human metapneumovirus increased from 6.6% (153), 9.9% (229), and 0.5% (12) in 2019 to 25.6% (873), 15.5% (530), and 7.2% (247) in 2020, respectively (p < 0.0001).

Conclusions

Successful containment of seasonal influenza as a result of COVID-19 control measures will ensure we are better equipped to deal with future outbreaks of both influenza and COVID-19.Caused by virus competition, the detection rates of Human respiratory syncytial virus, Human parainfluenza virus, and Human metapneumovirus increased in Shenzhen,that reminds us we need to take further monitoring and preventive measures in the next epidemic season.

A comparative study between the incidence and epidemiological features of Influenza-Like Illness and laboratory-confirmed COVID-19 cases in the Italian epicenter (Lombardy)

INTRODUCTION

In Lombardy, the influenza surveillance system relies on sentinel physicians that weekly report data on the number of Influenza-Like Illness (ILI) and a part of them also collect nasopharyngeal samples for virologic analyses. This study aims at comparing the ILI incidence of 2019-2020 influenza season with the incidence of COVID-19 cases in order to better understand the current epidemic and to evaluate whether the implementation of ILI surveillance system could succeed in early detection and monitoring of COVID-19 diffusion.

METHODS

The distribution of ILI cases in the seasons 2017-2018, 2018-2019 and 2019-2020 was taken in consideration and the curve trends were compared and analyzed according to geographical areas, age groups and time differences.

RESULTS

The curve trends presented a similar pattern up to the 9th week; in fact, a reduction in the ILI incidence rate was observed in the 2017-2018 and 2018-2019 season but in the 2019-2020 an increase in the reported ILI emerged. The relation between the numbers reported by 2019-2020 ILI surveillance and those reported for COVID-19 is supported by the curve trends, the correspondence between age groups, the correspondence by geographical location, and also by the results of the nasopharyngeal swab tests performed.

DISCUSSION

The influenza surveillance system is an effective tool for early detection of COVID-19. It may provide timely and high-quality data evaluating the SARS-CoV-2 burden among population with ILI. Implementation of the system has to be prioritized in order to identify any future novel respiratory pathogen with pandemic potential.

When the COVID-19 Pandemic Surges during Influenza Season: Lessons Learnt from the Sentinel Laboratory-Based Surveillance of Influenza-Like Illness in Lombardy during the 2019-2020 Season

This paper outlines the role of Lombardy’s regional influenza reference laboratory (Northern Italy) in the surveillance of influenza-like illnesses (ILIs) in monitoring SARS-CoV-2 circulation by analyzing 631 consecutive nasopharyngeal swabs (NPSs) collected from ILI outpatients by sentinel physicians during the 2019–2020 season. The samples were tested by specific real-time RT-PCRs targeting SARS-CoV-2, influenza viruses, and RSVs. Results: Of these NPSs, 31% tested positive for influenza viruses, 10% for SARS-CoV-2, and 7% for RSV. No coinfections were detected. Influenza viruses and RSVs circulated throughout the surveillance period until the end of February (week 9-2020), when they suddenly ceased to circulate seven weeks earlier than during the previous five influenza seasons. After the first detection of SARS-CoV-2 in our ILI outpatients at the beginning of March (week 10-2020), SARS-CoV-2 remained the only virus identified throughout the surveillance period. Patients ≥ 65 years had a 3.2-fold greater risk of being infected with SARS-CoV-2, while school-age children (5–14 years) and children < 5 years proved to be the age groups most at risk of contracting influenza viruses and RSV, respectively. Our experience demonstrates that laboratory-based ILI surveillance networks are essential for identifying SARS-CoV-2 cases that would otherwise remain undetected, in order to stop their spread within our communities.

Cumulative Effects of Particulate Matter Pollution and Meteorological Variables on the Risk of Influenza-Like Illness

The cold season is usually accompanied by an increased incidence of respiratory infections and increased air pollution from combustion sources. As we are facing growing numbers of COVID-19 cases caused by the novel SARS-CoV-2 coronavirus, an understanding of the impact of air pollutants and meteorological variables on the incidence of respiratory infections is crucial. The incidence of influenza-like illness (ILI) can be used as a close proxy for the circulation of influenza viruses. Recently, SARS-CoV-2 has also been detected in patients with ILI. Using distributed lag nonlinear models, we analyzed the association between ILI, meteorological variables and particulate matter concentration in Bialystok, Poland, from 2013–2019. We found an exponential relationship between cumulative PM_2.5 pollution and the incidence of ILI, which remained significant after adjusting for air temperatures and a long-term trend. Pollution had the greatest effect during the same week, but the risk of ILI was increased for the four following weeks. The risk of ILI was also increased by low air temperatures, low absolute humidity, and high wind speed. Altogether, our results show that all measures implemented to decrease PM_2.5 concentrations would be beneficial to reduce the transmission of SARS-CoV-2 and other respiratory infections.

Modelling safe protocols for reopening schools during the COVID-19 pandemic in France

As countries in Europe implement strategies to control the COVID-19 pandemic, different options are chosen regarding schools. Through a stochastic age-structured transmission model calibrated to the observed epidemic in Île-de-France in the first wave, we explored scenarios of partial, progressive, or full school reopening. Given the uncertainty on children's role, we found that reopening schools after lockdown may increase COVID-19 cases, yet protocols exist to keep the epidemic controlled. Under a scenario with stable epidemic activity if schools were closed, reopening pre-schools and primary schools would lead to up to 76% [67, 84]% occupation of ICU beds if no other school level reopened, or if middle and high schools reopened later. Immediately reopening all school levels may overwhelm the ICU system. Priority should be given to pre- and primary schools allowing younger children to resume learning and development, whereas full attendance in middle and high schools is not recommended for stable or increasing epidemic activity. Large-scale test and trace is required to keep the epidemic under control. Ex-post assessment shows that progressive reopening of schools, limited attendance, and strong adoption of preventive measures contributed to a decreasing epidemic after lifting the first lockdown.

Impact of the lockdown on the burden of COVID-19 in outpatient care in France, spring 2020

BACKGROUND

To limit the spread of SARS-CoV-2 several countries implemented measures to reduce the number of contacts such as a national lockdown. We estimated the impact of the first lockdown on the burden of COVID-19 in the community in France.

METHODS

Physicians participating in the French Sentinelles network reported the number of patients with an acute respiratory infection (ARI) seen in consultation and performed nasopharyngeal swabs in a sample of these patients (first patient of the week). The swabs were tested by RT-PCR for the presence of SARS-CoV-2. Clinical and virological data were combined to estimate ARI incidence attributable to SARS-CoV-2 from 17 March to 10 May 2020.

RESULTS

The incidence of ARI attributable to COVID-19 decreased after the second week of the lockdown period from 142 (95%CI [101; 183]) to 41 (95%CI [21; 60]) per 100,000 population. A decrease was observed in all areas in metropolitan France. The youngest age groups (<15-years-old) were least affected with a cumulated incidence estimated to 14 per 100,000 population during the study period.

CONCLUSIONS

The data collected in primary care suggests that the first lockdown implemented in France during spring 2020 significantly reduced the incidence of acute respiratory infections including COVID-19 in France and limited the geographic spread of SARS-CoV-2.

Early indicators of intensive care unit bed requirement during the COVID-19 epidemic: A retrospective study in Ile-de-France region, France

The aim of our retrospective study was to evaluate the earliest COVID19-related signal to anticipate requirements of intensive care unit (ICU) beds. Although the number of ICU beds is crucial during the COVID-19 epidemic, there is no recognized early indicator to anticipate it. In the Ile-de-France region, from February 20 to May 5, 2020, emergency medical service (EMS) calls and the response provided (ambulances) together the percentage of positive reverse transcriptase polymerase chain reaction (RT-PCR) tests, general practitioner (GP) and emergency department (ED) visits, and hospital admissions of COVID-19 patients were recorded daily and compared to the number of ICU patients. Correlation curve analysis was performed to determine the best correlation coefficient, depending on the number of days the indicator has been shifted. Primary endpoint was the number of ICU patients. EMS calls, percentage of positive RT-PCR tests, ambulances used, ED and GP visits of COVID-19 patients were strongly associated (R² ranging between 0.79 to 0.99, all P<0.001) with COVID-19 ICU patients with an anticipation delay of 23, 15, 14, 13, and 12 days respectively. Hospitalization did not anticipate ICU bed requirement. A qualitative analysis of the onset of the second wave period of the epidemic (August 1 to September 15, 2020) in the same region provided similar results. The daily number of COVID19-related telephone calls received by the EMS and corresponding dispatch ambulances, and the proportion of positive RT-PCR tests were the earliest indicators of the number of COVID19 patients requiring ICU care during the epidemic crisis, rapidly followed by ED and GP visits. This information may help health authorities to anticipate a future epidemic, including a second wave of COVID19, or decide additional social measures.

Simple Questionnaires to Improve Pooling Strategies for SARS-CoV-2 Laboratory Testing

Background:

Liberal PCR testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is key to contain the coronavirus disease 2019 (COVID-19) pandemic. Combined multi-sample testing in pools instead of single tests might enhance laboratory capacity and reduce costs, especially in low- and middle-income countries.

Objective:

The purpose of our study was to assess the value of a simple questionnaire to guide and further improve pooling strategies for SARS-CoV-2 laboratory testing.

Methods:

Pharyngeal swabs for SARS-CoV-2 testing were obtained from healthcare and police staff, hospital inpatients, and nursing home residents in the southwestern part of Germany. We designed a simple questionnaire, which included questions pertaining to a suggestive clinical symptomatology, recent travel history, and contact with confirmed cases to stratify an individual’s pre-test probability of having contracted COVID-19. The questionnaire was adapted repeatedly in face of the unfolding pandemic in response to the evolving epidemiology and observed clinical symptomatology. Based on the response patterns, samples were either tested individually or in multi-sample pools. We compared the pool positivity rate and the number of total PCR tests required to obtain individual results between this questionnaire-based pooling strategy and randomly assembled pools.

Findings:

Between March 11 and July 5, 2020, we processed 25,978 samples using random pooling (n = 6,012; 23.1%) or questionnaire-based pooling (n = 19,966; 76.9%). The overall prevalence of SARS-CoV-2 was 0.9% (n = 238). Pool positivity (14.6% vs. 1.2%) and individual SARS-CoV-2 prevalence (3.4% vs. 0.1%) were higher in the random pooling group than in the questionnaire group. The average number of PCR tests needed to obtain the individual result for one participant was 0.27 tests in the random pooling group, as compared to 0.09 in the questionnaire-based pooling group, leading to a laboratory capacity increase of 73% and 91%, respectively, as compared to single PCR testing.

Conclusions:

Strategies that combine pool testing with a questionnaire-based risk stratification can increase laboratory testing capacities for COVID-19 and might be important tools, particularly in resource-constrained settings.

Collider bias undermines our understanding of COVID-19 disease risk and severity

Numerous observational studies have attempted to identify risk factors for infection with SARS-CoV-2 and COVID-19 disease outcomes. Studies have used datasets sampled from patients admitted to hospital, people tested for active infection, or people who volunteered to participate. Here, we highlight the challenge of interpreting observational evidence from such non-representative samples. Collider bias can induce associations between two or more variables which affect the likelihood of an individual being sampled, distorting associations between these variables in the sample. Analysing UK Biobank data, compared to the wider cohort the participants tested for COVID-19 were highly selected for a range of genetic, behavioural, cardiovascular, demographic, and anthropometric traits. We discuss the mechanisms inducing these problems, and approaches that could help mitigate them. While collider bias should be explored in existing studies, the optimal way to mitigate the problem is to use appropriate sampling strategies at the study design stage.

Les indicateurs d’alerte et de surveillance de la Covid-19

Face à la crise sanitaire provoquée par la pandémie de Covid-19 en France, Santé publique France a mis en place un système de surveillance évolutif fondé sur des définitions de cas possible, probable et confirmé. Le décompte quotidien se limite cependant aux cas confirmés par reverse transcriptase polymerase chain reaction ou sérologie SARS-CoV-2 (actuellement via la plateforme SI-DEP), aux cas hospitalisés (via le Système d’information pour le suivi des victimes d’attentats) et aux décès hospitaliers par Covid-19. Ce suivi de la circulation virale est forcément non exhaustif, et l’estimation de l’incidence est complétée par d’autres indicateurs comme les appels au 15, les recours à SOS Médecins, les passages dans les services d’accueil des urgences, les consultations de médecine de ville via le réseau Sentinelle. Le suivi de la mortalité non hospitalière s’est heurté aux délais de transmission des certificats de décès et au manque de diagnostic fiable. Seule la létalité hospitalière a pu être mesurée de manière fiable. Moyennant un certain nombre de précautions statistiques et d’hypothèses de travail, les modèles ont permis d’anticiper l’évolution de l’épidémie à partir de deux indicateurs essentiels : le ratio de reproduction R et le temps de doublement épidémique. En Île-de-France, l’Assistance publique– Hôpitaux de Paris a complété ce tableau de bord grâce à son entrepôt de données de santé et a ainsi pu modéliser de manière fine le parcours de soins des patients. L’ensemble de ces indicateurs a été essentiel pour assurer une planification de la réponse à la crise.

Identifying the outbreak signal of COVID-19 before the response of the traditional disease monitoring system

SYNOPSIS

Early identification of the emergence of an outbreak of a novel infectious disease is critical to generating a timely response. The traditional monitoring system is adequate for detecting the outbreak of common diseases; however, it is insufficient for the discovery of novel infectious diseases. In this study, we used COVID-19 as an example to compare the delay time of different tools for identifying disease outbreaks. The results showed that both the abnormal spike in influenza-like illnesses and the peak of online searches of key terms could provide early signals. We emphasize the importance of testing these findings and discussing the broader potential to use syndromic surveillance, internet searches, and social media data together with traditional disease surveillance systems for early detection and understanding of novel emerging infectious diseases.

Trajectories of Hospitalization in COVID-19 Patients: An Observational Study in France

Describing the characteristics of COVID-19 patients in the hospital is of importance to assist in the management of hospital capacity in the future. Here, we analyze the trajectories of 1321 patients admitted to hospitals in northern and eastern France. We found that the time from onset to hospitalization decreased with age, from 7.3 days in the 20-65 year-olds to 4.5 in the >80 year-olds (p < 0.0001). Overall, the length of stay in the hospital was 15.9 days, and the death rate was 20%. One patient out of four was admitted to the intensive care unit (ICU) for approximately one month. The characteristics of trajectories changed with age: fewer older patients were admitted to the ICU and the death rate was larger in the elderly. Admission shortly after onset was associated with increased mortality (odds-ratio (OR) = 1.8, Confidence Interval (CI) 95% [1.3, 2.6]) as well as male sex (OR = 2.1, CI 95% [1.5, 2.9]). Time from admission within the hospital to the transfer to ICU was short. The age- and sex-adjusted mortality rate decreased over the course of the epidemic, suggesting improvement in care over time. In the SARS-CoV-2 epidemic, the urgent need for ICU at admission and the prolonged length of stay in ICU are a challenge for bed management and organization of care.

Ecologic association between influenza and COVID-19 mortality rates in European countries

Ecologic studies investigating COVID-19 mortality determinants, used to make predictions and design public health control measures, generally focused on population-based variable counterparts of individual-based risk factors. Influenza is not causally associated with COVID-19, but shares population-based determinants, such as similar incidence/mortality trends, transmission patterns, efficacy of non-pharmaceutical interventions, comorbidities and underdiagnosis. We investigated the ecologic association between influenza mortality rates and COVID-19 mortality rates in the European context. We considered the 3-year average influenza (2014-2016) and COVID-19 (31 May 2020) crude mortality rates in 34 countries using EUROSTAT and ECDC databases and performed correlation and regression analyses. The two variables - log transformed, showed significant Spearman's correlation ρ = 0.439 (P = 0.01), and regression coefficients, b = 0.743 (95% confidence interval, 0.272-1.214; R2 = 0.244; P = 0.003), b = 0.472 (95% confidence interval, 0.067-0.878; R2 = 0.549; P = 0.02), unadjusted and adjusted for confounders (population size and cardiovascular disease mortality), respectively. Common significant determinants of both COVID-19 and influenza mortality rates were life expectancy, influenza vaccination in the elderly (direct associations), number of hospital beds per population unit and crude cardiovascular disease mortality rate (inverse associations). This analysis suggests that influenza mortality rates were independently associated with COVID-19 mortality rates in Europe, with implications for public health preparedness, and implies preliminary undetected SARS-CoV-2 spread in Europe.

Tracking the onset date of the community spread of SARS-CoV-2 in western countries

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) rapidly spread around the world during 2020, but the precise time in which the virus began to spread locally is difficult to trace for most countries. Here, we estimate the probable onset date of the community spread of SARS-CoV-2 for heavily affected countries from Western Europe and the Americas on the basis of the cumulative number of deaths reported during the early stage of the epidemic. Our results support that SARS-CoV-2 probably started to spread locally in all western countries analysed between mid-January and mid-February 2020, thus long before community transmission was officially recognised and control measures were implemented.

Using influenza surveillance networks to estimate state-specific prevalence of SARS-CoV-2 in the United States

Detection of SARS-CoV-2 infections to date has relied heavily on RT-PCR testing. However, limited test availability, high false-negative rates, and the existence of asymptomatic or sub-clinical infections have resulted in an under-counting of the true prevalence of SARS-CoV-2. Here, we show how influenza-like illness (ILI) outpatient surveillance data can be used to estimate the prevalence of SARS-CoV-2. We found a surge of non-influenza ILI above the seasonal average in March 2020 and showed that this surge correlated with COVID-19 case counts across states. If 1/3 of patients infected with SARS-CoV-2 in the US sought care, this ILI surge would have corresponded to more than 8.7 million new SARS-CoV-2 infections across the US during the three-week period from March 8 to March 28, 2020. Combining excess ILI counts with the date of onset of community transmission in the US, we also show that the early epidemic in the US was unlikely to have been doubling slower than every 4 days. Together these results suggest a conceptual model for the COVID-19 epidemic in the US characterized by rapid spread across the US with over 80% infected patients remaining undetected. We emphasize the importance of testing these findings with seroprevalence data and discuss the broader potential to use syndromic surveillance for early detection and understanding of emerging infectious diseases.