Risk Diagrams Based on Primary Care Electronic Medical Records and Linked Real-Time PCR Data to Monitor Local COVID-19 Outbreaks During the Summer 2020: A Prospective Study Including 7,671,862 People in Catalonia

Mathematical modeling of SARS-CoV-2 variant substitutions in European countries: transmission dynamics and epidemiological insights

Background

Countries across Europe have faced similar evolutions of SARS-CoV-2 variants of concern, including the Alpha, Delta, and Omicron variants.

Materials and methods

We used data from GISAID and applied a robust, automated mathematical substitution model to study the dynamics of COVID-19 variants in Europe over a period of more than 2 years, from late 2020 to early 2023. This model identifies variant substitution patterns and distinguishes between residual and dominant behavior. We used weekly sequencing data from 19 European countries to estimate the increase in transmissibility  ( Δ β )   between consecutive SARS-CoV-2 variants. In addition, we focused on large countries with separate regional outbreaks and complex scenarios of multiple competing variants.

Results

Our model accurately reproduced the observed substitution patterns between the Alpha, Delta, and Omicron major variants. We estimated the daily variant prevalence and calculated Δ β between variants, revealing that: ( i ) Δ β increased progressively from the Alpha to the Omicron variant; ( i i ) Δ β showed a high degree of variability within Omicron variants; ( i i i ) a higher Δ β was associated with a later emergence of the variant within a country; ( i v ) a higher degree of immunization of the population against previous variants was associated with a higher Δ β for the Delta variant; ( v ) larger countries exhibited smaller Δ β ,  suggesting regionally diverse outbreaks within the same country; and finally ( v i ) the model reliably captures the dynamics of competing variants, even in complex scenarios.

Conclusion

The use of mathematical models allows for precise and reliable estimation of daily cases of each variant. By quantifying Δ β ,  we have tracked the spread of the different variants across Europe, highlighting a robust increase in transmissibility trend from Alpha to Omicron. Additionally, we have shown that the geographical characteristics of a country, as well as the timing of new variant entrances, can explain some of the observed differences in variant substitution dynamics across countries.

Country-report pattern corrections of new cases allow accurate 2-week predictions of COVID-19 evolution with the Gompertz model

Accurate short-term predictions of COVID-19 cases with empirical models allow Health Officials to prepare for hospital contingencies in a two-three week window given the delay between case reporting and the admission of patients in a hospital. We investigate the ability of Gompertz-type empiric models to provide accurate prediction up to two and three weeks to give a large window of preparation in case of a surge in virus transmission. We investigate the stability of the prediction and its accuracy using bi-weekly predictions during the last trimester of 2020 and 2021. Using data from 2020, we show that understanding and correcting for the daily reporting structure of cases in the different countries is key to accomplish accurate predictions. Furthermore, we found that filtering out predictions that are highly unstable to changes in the parameters of the model, which are roughly 20%, reduces strongly the number of predictions that are way-off. The method is then tested for robustness with data from 2021. We found that, for this data, only 1-2% of the one-week predictions were off by more than 50%. This increased to 3% for two-week predictions, and only for three-week predictions it reached 10%.

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.

A semi-empirical risk panel to monitor epidemics: multi-faceted tool to assist healthcare and public health professionals

Introduction

Bronchiolitis, mostly caused by Respiratory Syncytial Virus (RSV), and influenza among other respiratory infections, lead to seasonal saturation at healthcare centers in temperate areas. There is no gold standard to characterize the stages of epidemics, nor the risk of respiratory infections growing. We aimed to define a set of indicators to assess the risk level of respiratory viral epidemics, based on both incidence and their short-term dynamics, and considering epidemical thresholds.

Methods

We used publicly available data on daily cases of influenza for the whole population and bronchiolitis in children <2 years from the Information System for Infection Surveillance in Catalonia (SIVIC). We included a Moving Epidemic Method (MEM) variation to define epidemic threshold and levels. We pre-processed the data with two different nowcasting approaches and performed a 7-day moving average. Weekly incidences (cases per 105 population) were computed and the 5-day growth rate was defined to create the effective potential growth (EPG) indicator. We performed a correlation analysis to define the forecasting ability of this index.

Results

Our adaptation of the MEM method allowed us to define epidemic weekly incidence levels and epidemic thresholds for bronchiolitis and influenza. EPG was able to anticipate daily 7-day cumulative incidence by 4-5 (bronchiolitis) or 6-7 (influenza) days.

Discussion

We developed a semi-empirical risk panel incorporating the EPG index, which effectively anticipates surpassing epidemic thresholds for bronchiolitis and influenza. This panel could serve as a robust surveillance tool, applicable to respiratory infectious diseases characterized by seasonal epidemics, easy to handle for individuals lacking a mathematical background.

Mortality in Catalonia during the summer of 2022 and its relation with high temperatures and COVID-19 cases

Purpose

To analyse the association between the mortality during the summer 2022 and either high temperatures or the COVID-19 wave with data from the Catalan Health Care System (7.8 million people).

Methods

We performed a retrospective study using publicly available data of meteorological variables, influenza-like illness (ILI) cases (including COVID-19) and deaths. The study comprises the summer months of the years 2021 and 2022. To compare the curves of mortality, ILI and temperature we calculated the z-score of each series. We assessed the observed lag between curves using the cross-correlation function. Finally, we calculated the correlation between the z-scores using the Pearson correlation coefficient (R²).

Results

During the study period, 33,967 deaths were reported in Catalonia (16,416 in the summer of 2021 and 17,551 in the summer of 2022). In 2022, the observed lag and the correlation between the z-scores of temperature and all-cause deaths was 3 days and R² = 0.86, while between ILI and all-cause deaths was 22 days and R² = 0.21. This high correlation between temperature and deaths increased up to 0.91 when we excluded those deaths reported as COVID-19 deaths, while the correlation between ILI and non-COVID-19 deaths decreased to -0.19. No correlation was observed between non-COVID deaths and temperature or ILI cases in 2021.

Conclusion

Our study suggests that the main cause of the increase in deaths during summer 2022 in Catalonia was the high temperatures and its duration. The contribution of the COVID-19 seems to be limited.

Transmissibility, hospitalization, and intensive care admissions due to omicron compared to delta variants of SARS-CoV-2 in Catalonia: A cohort study and ecological analysis

Purpose

We aim to compare the severity of infections between omicron and delta variants in 609,352 SARS-CoV-2 positive cases using local hospitalization, vaccination, and variants data from the Catalan Health Care System (which covers around 7. 8 million people).

Methods

We performed a substitution model to establish the increase in transmissibility of omicron using variant screening data from primary care practices (PCP) and hospital admissions. In addition, we used this data from PCP to establish the two periods when delta and omicron were, respectively, dominant (above 95% of cases). After that, we performed a population-based cohort analysis to calculate the rates of hospital and intensive care unit (ICU) admissions for both periods and to estimate reduction in severity. Rate ratios (RR) and 95% confidence intervals (95% CI) were calculated and stratified by age and vaccination status. In a second analysis, the differential substitution model in primary care vs. hospitals allowed us to obtain a population-level average change in severity.

Results

We have included 48,874 cases during the delta period and 560,658 during the omicron period. During the delta period, on average, 3.8% of the detected cases required hospitalization for COVID-19. This percentage dropped to 0.9% with omicron [RR of 0.46 (95% CI: 0.43 to 0.49)]. For ICU admissions, it dropped from 0.8 to 0.1% [RR 0.25 (95% CI: 0.21 to 0.28)]. The proportion of cases hospitalized or admitted to ICU was lower in the vaccinated groups, independently of the variant. Omicron was associated with a reduction in risk of admission to hospital and ICU in all age and vaccination status strata. The differential substitution models showed an average RR between 0.19 and 0.50.

Conclusion

Both independent methods consistently show an important decrease in severity for omicron relative to delta. The systematic reduction happens regardless of age. The severity is also reduced for non-vaccinated and vaccinated groups, but it remains always higher in the non-vaccinated population. This suggests an overall reduction in severity, which could be intrinsic to the omicron variant. The fact is that the RR in ICU admission is systematically smaller than in hospitalization points in the same direction.

Comparing the first and second waves of COVID-19 in a tertiary university hospital in Barcelona

BACKGROUND

Hospitals have constituted the limiting resource of the healthcare systems for the management of the COVID-19 pandemic. As the pandemic progressed, knowledge of the disease improved, and healthcare systems were expected to be more adapted to provide a more efficient response. The objective of this research was to compare the flow of COVID-19 patients in emergency rooms and hospital wards, between the pandemic's first and second waves at the University Hospital of Vall d'Hebron (Barcelona, Spain), and to compare the profiles, severity and mortality of COVID-19 patients between the two waves.

METHODS

A retrospective observational analysis of COVID-19 patients attending the hospital from February 24 to April 26, 2020 (first wave) and from July 24, 2020, to May 18, 2021 (second wave) was carried out. We analysed the data of the electronic medical records on patient demographics, comorbidity, severity, and mortality.

RESULTS

The daily number of COVID-19 patients entering the emergency rooms (ER) dropped by 65% during the second wave compared to the first wave. During the second wave, patients entering the ER were significantly younger (61 against 63 years old p<0.001) and less severely affected (39% against 48% with a triage level of resuscitation or emergency; p<0.001). ER mortality declined during the second wave (1% against 2%; p<0.000). The daily number of hospitalised COVID-19 patients dropped by 75% during the second wave. Those hospitalised during the second wave were more severely affected (20% against 10%; p<0.001) and were referred to the intensive care unit (ICU) more frequently (21% against 15%; p<0.001). Inpatient mortality showed no significant difference between the two waves.

CONCLUSIONS

Changes in the flow, severity and mortality of COVID-19 patients entering this tertiary hospital during the two waves may reflect a better adaptation of the health care system and the improvement of knowledge on the disease.

The impact of prioritisation and dosing intervals on the effects of COVID-19 vaccination in Europe: an agent-based cohort model

Different strategies have been used to maximise the effect of COVID-19 vaccination campaigns in Europe. We modelled the impact of different prioritisation choices and dose intervals on infections, hospitalisations, mortality, and public health restrictions. An agent-based model was built to quantify the impact of different vaccination strategies over 6 months. Input parameters were derived from published phase 3 trials and official European figures. We explored the effect of prioritising vulnerable people, care-home staff and residents, versus contagious groups; and the impact of dose intervals ranging from 3 to 12 weeks. Prioritising vulnerable people, rather than the most contagious, led to higher numbers of COVID-19 infections, whilst reducing mortality, hospital admissions, and public health restrictions. At a realistic vaccination speed of ≤ 0·1% population/day, separating doses by 12 weeks (vs a baseline scenario of 3 weeks) reduced hospitalisations, mortality, and restrictions for vaccines with similar first- and second-dose efficacy (e.g., the Oxford-AstraZeneca and Moderna vaccines), but not for those with lower first vs second-dose efficacy (e.g., the Pfizer/BioNTech vaccine). Mass vaccination will dramatically reduce the effect of COVID-19 on Europe's health and economy. Early vaccination of vulnerable populations will reduce mortality, hospitalisations, and public health restrictions compared to prioritisation of the most contagious people. The choice of interval between doses should be based on expected vaccine availability and first-dose efficacy, with 12-week intervals preferred over shorter intervals in most realistic scenarios.