Investigation of a COVID-19 outbreak in Germany resulting from a single travel-associated primary case: a case series

Substantial transmission of SARS-CoV-2 through casual contact in retail stores: Evidence from matched administrative microdata on card payments and testing

This paper presents quasiexperimental evidence of Covid-19 transmission through casual contact between customers in retail stores. For a large sample of individuals in Denmark, we match card payment data, indicating exactly where and when each individual made purchases, with Covid-19 test data, indicating when each individual was tested and whether the test was positive. The resulting dataset identifies more than 100,000 instances where an infected individual made a purchase in a store and, in each instance, allows us to track the infection dynamics of other individuals who made purchases in the same store around the same time. We estimate transmissions by comparing the infection rate of exposed customers, who made a purchase within 5 min of an infected individual, and nonexposed customers, who made a purchase in the same store 16 to 30 min before. We find that exposure to an infected individual in a store increases the infection rate by around 0.12 percentage points (P < 0.001) between day 3 and day 7 after exposure. The estimates imply that transmissions in stores contributed around 0.04 to the reproduction number for the average infected individual and significantly more in the period where Omicron was the dominant variant.

How robust are estimates of key parameters in standard viral dynamic models?

Mathematical models of viral infection have been developed, fitted to data, and provide insight into disease pathogenesis for multiple agents that cause chronic infection, including HIV, hepatitis C, and B virus. However, for agents that cause acute infections or during the acute stage of agents that cause chronic infections, viral load data are often collected after symptoms develop, usually around or after the peak viral load. Consequently, we frequently lack data in the initial phase of viral growth, i.e., when pre-symptomatic transmission events occur. Missing data may make estimating the time of infection, the infectious period, and parameters in viral dynamic models, such as the cell infection rate, difficult. However, having extra information, such as the average time to peak viral load, may improve the robustness of the estimation. Here, we evaluated the robustness of estimates of key model parameters when viral load data prior to the viral load peak is missing, when we know the values of some parameters and/or the time from infection to peak viral load. Although estimates of the time of infection are sensitive to the quality and amount of available data, particularly pre-peak, other parameters important in understanding disease pathogenesis, such as the loss rate of infected cells, are less sensitive. Viral infectivity and the viral production rate are key parameters affecting the robustness of data fits. Fixing their values to literature values can help estimate the remaining model parameters when pre-peak data is missing or limited. We find a lack of data in the pre-peak growth phase underestimates the time to peak viral load by several days, leading to a shorter predicted growth phase. On the other hand, knowing the time of infection (e.g., from epidemiological data) and fixing it results in good estimates of dynamical parameters even in the absence of early data. While we provide ways to approximate model parameters in the absence of early viral load data, our results also suggest that these data, when available, are needed to estimate model parameters more precisely.

Symptoms and Severity of COVID-19 in Patients with Immune-Mediated Inflammatory Diseases: Experience of a University Medical Center

Background

The pandemic situation of the novel coronavirus (severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)) and its associated disease (coronavirus disease 2019 (COVID-19)) represents a challenging condition with a plethora of aspects. The course of COVID-19 in patients with immune-mediated inflammatory diseases (IMID) such as inflammatory bowel disease (IBD) and rheumatic diseases (RD) is not well known. Our study is one step toward closing this gap by collecting data on vaccination rates, infection-free survival, and individual symptom severity.

Methods

We conducted a prospective questionnaire-based study between April 2022 and October 2022 at our university hospital. Outward patients over the age of 18 years were screened for participation and reported about their infection/infection-free survival since the start of the pandemic.

Results

Finally, 156 patients were included in the study, 117 (75.0%) of which had inflammatory bowel disease and 39 (25.0%) patients with rheumatic disease. Altogether, 143 (91.7%) persons had received at least one vaccination against SARS-CoV-2. A total of 153 patients provided information regarding their COVID-19 history: 81 patients (52.0%) self-reported about their SARS-CoV-2 infection. In general, courses of infection were mild: only two patients (2.5% of patients with reported COVID-19) were hospitalized due to COVID-19 with one (1.2%) of the two needing intensive care. Asymptomatic COVID-19 had been described by 7 persons (8.6% of patients with reported COVID-19). Acute COVID-19 was accompanied by fatigue/tiredness in 58 persons (71.6% of patients with history of COVID-19) as the most frequent symptom. Other complaints were common cold (55 patients = 67.9%), cough (51 patients = 63.0%), headache (44 patients = 54.3%), and fever (35 patients = 43.2%). Stratified by vaccination status (unvaccinated vs. at least once vaccinated), the time to infection differed significantly (logrank test: p = 0.04, Chi2 4.1). At least once vaccinated people had a median COVID-19-free survival of 28.5 months (confidence interval (CI): 23.6 months-not reached). Without any vaccination, the estimated time to infection was 25.1 months (CI: 23.6 months-not reached).

Conclusion

Our IMID patients have a high rate of vaccination against SARS-CoV-2. Data show a significantly longer infection-free survival in vaccinated IMID patients as compared to unvaccinated patients. Discrimination between symptoms of COVID-19 and a concomitant inflammatory disease is difficult as complaints might be overlapping. This trial is registered with DRKS00028880.

Evolutionary trajectory of diverse SARS-CoV-2 variants at the beginning of COVID-19 outbreak

Despite extensive scientific efforts directed toward the evolutionary trajectory of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in humans at the beginning of the COVID-19 epidemic, it remains unclear how the virus jumped into and evolved in humans so far. Herein, we recruited almost all adult coronavirus disease 2019 (COVID-19) cases appeared locally or imported from abroad during the first 8 months of the outbreak in Shanghai. From these patients, SARS-CoV-2 genomes occupying the important phylogenetic positions in the virus phylogeny were recovered. Phylogenetic and mutational landscape analyses of viral genomes recovered here and those collected in and outside of China revealed that all known SARS-CoV-2 variants exhibited the evolutionary continuity despite the co-circulation of multiple lineages during the early period of the epidemic. Various mutations have driven the rapid SARS-CoV-2 diversification, and some of them favor its better adaptation and circulation in humans, which may have determined the waxing and waning of various lineages.

The impact of vaccination and SARS-CoV-2 variants on the virological response to SARS-CoV-2 infections during the Alpha, Delta, and Omicron waves in England

Vaccination status and the SARS-CoV-2 variant individuals are infected with are known to independently impact viral dynamics; however, little is known about the interaction of these two factors and how this impacts viral dynamics. Here we investigated how monovalent vaccination modified the time course and viral load of infections from different variants. Regression analyses were used to investigate the impact of vaccination on cycle threshold values and disease severity, and interval-censored survival analyses were used to investigate the impact of vaccination on duration of positivity. A range of covariates were adjusted for as potential confounders and investigated for their own effects in exploratory analyses. All analyses were done combining all variants and stratified by variant. For those infected with Alpha or Delta, vaccinated individuals were more likely to report mild disease than moderate/severe disease and had significantly shorter duration of positivity and lower viral loads compared to unvaccinated individuals. Vaccination had no impact on self-reported disease severity, viral load, or duration if positivity for those infected with Omicron. Overall, individuals who were immunosuppressed and clinically extremely vulnerable had longer duration of positivity and higher viral loads. This study adds to the evidence base on disease dynamics following COVID-19, demonstrating that vaccination mitigates severity of disease, the amount of detectable virus within infected individuals and reduces the time individuals are positive for. However, these effects have been significantly attenuated since the emergence of Omicron. Therefore, our findings strengthen the argument for using modified or multivalent vaccines that target emerging variants.

Effects of the COVID-19 pandemic on life expectancy and premature mortality in the German federal states in 2020 and 2021

The mortality impact of COVID-19 has mainly been studied at the national level. However, looking at the aggregate impact of the pandemic at the country level masks heterogeneity at the subnational level. Subnational assessments are essential for the formulation of public health policies. This is especially important for federal countries with decentralised healthcare systems, such as Germany. Therefore, we assess geographical variation in the mortality impact of COVID-19 for the 16 German federal states in 2020 and 2021 and the sex differences therein. For this purpose, we adopted an ecological study design, using population-level mortality data by federal state, age, and sex, for 2005-2021 obtained from the German Federal Statistical Office. We quantified the impact of the pandemic using the excess mortality approach. We estimated period life expectancy losses (LE losses), excess premature mortality, and excess deaths by comparing their observed with their expected values. The expected mortality was based on projected age-specific mortality rates using the Lee-Carter methodology. Saxony was the most affected region in 2020 (LE loss 0.77 years, 95% CI 0.74;0.79) while Saarland was the least affected (-0.04, -0.09;0.003). In 2021, the regions with the highest losses were Thuringia (1.58, 1.54;1.62) and Saxony (1.57, 1.53;1.6) and the lowest in Schleswig-Holstein (0.13, 0.07;0.18). Furthermore, in 2021, eastern regions experienced higher LE losses (mean: 1.13, range: 0.85 years) than western territories (mean: 0.5, range: 0.72 years). The regional variation increased between 2020 and 2021, and was higher among males than among females, particularly in 2021. We observed an unequal distribution of the mortality impact of COVID-19 at the subnational level in Germany, particularly in 2021 among the male population. The observed differences between federal states might be partially explained by the heterogeneous spread of the virus in 2020 and by differences in the population's propensity to follow preventive guidelines.

Neighbourhood watch: genomic epidemiology of SARS-CoV-2 variants circulating in a German federal state, Mecklenburg-Western Pomerania, in 2020-2022

ABSTRACTGlobal and even national genome surveillance approaches do not provide the resolution necessary for rapid and accurate direct response by local public health authorities. Hence, a regional network of microbiological laboratories in collaboration with the health departments of all districts of the German federal state of Mecklenburg-Western Pomerania (M-V) was formed to investigate the regional molecular epidemiology of circulating SARS-CoV-2 lineages between 11/2020 and 03/2022. More than 4750 samples from all M-V counties were sequenced using Illumina and Nanopore technologies. Overall, 3493 (73.5%) sequences fulfilled quality criteria for time-resolved and/or spatially-resolved maximum likelihood phylogenic analyses and k-mean/ median clustering (KMC). We identified 116 different Pangolin virus lineages that can be assigned to 16 Nextstrain clades. The ten most frequently detected virus lineages belonged to B.1.1.7, AY.122, AY.43, BA.1, B.1.617.2, BA.1.1, AY.9.2, AY.4, P.1 and AY.126. Time-resolved phylogenetic analyses showed the occurrence of virus clades as determined worldwide, but with a substantial delay of one to two months. Further spatio-temporal phylogenetic analyses revealed a regional outbreak of a Gamma variant limited to western M-V counties. Finally, KMC elucidated a successive introduction of the various virus lineages into M-V, possibly triggered by vacation periods with increased (inter-) national travel activities. The COVID-19 pandemic in M-V was shaped by a combination of several SARS-CoV-2 introductions, lockdown measures, restrictive quarantine of patients and the lineage specific replication rate. Complementing global and national surveillance, regional surveillance adds value by providing a higher level of surveillance resolution tailored to local health authorities.

[Influence of the COVID-19 pandemic on fracture epidemiology exemplified by tibial plateau fractures]

BACKGROUND

During the COVID-19 pandemic interventions, such as contact restrictions, lockdowns and postponement of elective surgeries were taken to ease the burden on the healthcare system. Among the population, these interventions led to changes in recreational behavior as well as personal transportation.

OBJECTIVE

This paper examines the epidemiological data of tibial plateau fractures (TPF) before and during the pandemic and to what extent pandemic control measures had an impact.

MATERIAL AND METHODS

In this retrospective monocentric study of a German level 1 trauma center, the intra-articular tibial plateau fractures of the years 2019 and 2020 were compared regarding incidence, demographics, cause of the accident, and treatment strategy. Fracture classification was according to Schatzker, AO/OTA, and Moore.

RESULTS

Incidence showed a decrease of -8.5% as well as a shift in the age incidence curves. There was a decrease in incidence during lockdown periods but also an increase in late summer 2020 compared to 2019. Tripping accidents (+12.4%) and bicycle accidents (+6.6%) increased in the pandemic year, whereas motorized traffic accidents (-7%) and skiing accidents (-10%) decreased. In terms of fracture morphology, 2020 showed an increase in impression fractures and a decrease in complex fractures. The number of surgically treated patients decreased by 7.3%.

CONCLUSION

The 12 months of pandemic resulted in only a slight incidence decrease of intra-articular tibial plateau fractures. The pandemic control measures showed effects within the calendar year and led directly and indirectly to a change in incidence, cause of the accident, fracture entities and care strategy.

Probiotics and prebiotics: potential prevention and therapeutic target for nutritional management of COVID-19?

Scientists are working to identify prevention/treatment methods and clinical outcomes of coronavirus disease 2019 (COVID-19). Nutritional status and diet have a major impact on the COVID-19 disease process, mainly because of the bidirectional interaction between gut microbiota and lung, that is, the gut-lung axis. Individuals with inadequate nutritional status have a pre-existing imbalance in the gut microbiota and immunity as seen in obesity, diabetes, hypertension and other chronic diseases. Communication between the gut microbiota and lungs or other organs and systems may trigger worse clinical outcomes in viral respiratory infections. Thus, this review addresses new insights into the use of probiotics and prebiotics as a preventive nutritional strategy in managing respiratory infections such as COVID-19 and highlighting their anti-inflammatory effects against the main signs and symptoms associated with COVID-19. Literature search was performed through PubMed, Cochrane Library, Scopus and Web of Science databases; relevant clinical articles were included. Significant randomised clinical trials suggest that specific probiotics and/or prebiotics reduce diarrhoea, abdominal pain, vomiting, headache, cough, sore throat, fever, and viral infection complications such as acute respiratory distress syndrome. These beneficial effects are linked with modulation of the microbiota, products of microbial metabolism with antiviral activity, and immune-regulatory properties of specific probiotics and prebiotics through Treg cell production and function. There is a need to conduct clinical and pre-clinical trials to assess the combined effect of consuming these components and undergoing current therapies for COVID-19.

Association of known SARS-CoV-2 serostatus and adherence to personal protection measures and the impact of personal protective measures on seropositivity in a population-based cross-sectional study (MuSPAD) in Germany

BACKGROUND

In 2020/2021 in Germany, several non-pharmacological interventions were introduced to lower the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We investigated to what extent knowledge of prior infection with SARS-CoV-2 or vaccination status influenced the use of personal protection measures (PPM). Further, we were interested in the effect of compliance with PPM on SARS-CoV-2 serostatus.

METHODS

Data was based on a sequential, multilocal seroprevalence study (MuSPAD), carried out in eight locations from July 2020 to August 2021. We estimated the association between a known SARS-CoV-2 serostatus (reported positive PCR test or vaccination) and self-reported PPM behavior (hand hygiene, physical distancing, wearing face mask), just as the association of PPM compliance with seropositivity against nucleocapsid (NC), receptor-binding domain (RBD), and spike protein (S) antigens. We identified relevant variables and deduced adjustment sets with directed acyclic graphs (DAG), and applied mixed logistic regression.

RESULTS

Out of the 22,297 participants (median age: 54 years, 43% male), 781 were classified as SARS-CoV-2-infected and 3,877 had a vaccinated immune response. Vaccinated individuals were less likely to keep 1.5 m distance [OR = 0.74 (95% CI: 0.57-0.97)] and only partly physically distanced [OR = 0.71 (95% CI: 0.58-0.87)]. Participants with self-reported positive PCR test had a lower chance of adhering partly to physical distancing [OR = 0.70 (95% CI: 0.50-0.99)] in comparison to the reference group. Higher odds of additionally wearing a face mask was observed in vaccinated [OR = 1.28 (95% CI: 1.08-1.51)] even if it was not obligatory. Overall, among unvaccinated participants, we found little evidence of lower odds of seropositivity given mask wearing [OR: 0.91 (95% CI: 0.71-1.16)], physical distancing [OR: 0.84 (95% CI: 0.59-1.20)] and no evidence for completely adhering to hand cleaning [OR: 0.97 (95% CI: 0.29-3.22)].

CONCLUSIONS

A known confirmed prior infection and vaccination may have the potential to influence adherence to PPM.

Increased blood pressure after nonsevere COVID-19

BACKGROUND

Various sequelae have been described after nonsevere coronavirus disease 2019 (COVID-19), but knowledge on postacute effects on blood pressure is limited.

METHODS

This is a cross-sectional analysis of blood pressure profiles in individuals after nonsevere COVID-19 compared with matched population-based individuals without prior COVID-19. Data were derived from the ongoing and prospective Hamburg City Health Study, a population-based study in Hamburg, Germany, and its associated COVID-19 program, which included individuals at least 4 months after COVID-19. Matching was performed by age, sex, education, and preexisting hypertension in a 1 : 4 ratio.

RESULTS

Four hundred and thirty-two individuals after COVID-19 (mean age 56.1 years) were matched to 1728 controls without prior COVID-19 (56.2 years). About 92.8% of COVID-19 courses were mild or moderate, only 7.2% were hospitalized, and no individual had been treated on an intensive care unit. Even after adjustment for relevant competing risk factors, DBP [+4.7 mmHg, 95% confidence interval (95% CI) 3.97-5.7, P  < 0.001] was significantly higher in individuals after COVID-19. For SBP, a trend towards increased values was observed (+1.4 mmHg, 95% CI -0.4 to 3.2, P  = 0.120). Hypertensive blood pressures at least 130/80 mmHg (according to the ACC/AHA guideline) and at least 140/90 mmHg (ESC/ESH guideline) occurred significantly more often in individuals after COVID-19 than matched controls (odds ratio 2.0, 95% CI 1.5-2.7, P  < 0.001 and odds ratio 1.6, 95% CI 1.3-2.0, P  < 0.001, respectively), mainly driven by changes in DBP.

CONCLUSION

Blood pressure is higher in individuals after nonsevere COVID-19 compared with uninfected individuals suggesting a significant hypertensive sequela.

Assessing changes in incubation period, serial interval, and generation time of SARS-CoV-2 variants of concern: a systematic review and meta-analysis

BACKGROUND

After the first COVID-19 wave caused by the ancestral lineage, the pandemic has been fueled from the continuous emergence of new SARS-CoV-2 variants. Understanding key time-to-event periods for each emerging variant of concern is critical as it can provide insights into the future trajectory of the virus and help inform outbreak preparedness and response planning. Here, we aim to examine how the incubation period, serial interval, and generation time have changed from the ancestral SARS-CoV-2 lineage to different variants of concern.

METHODS

We conducted a systematic review and meta-analysis that synthesized the estimates of incubation period, serial interval, and generation time (both realized and intrinsic) for the ancestral lineage, Alpha, Beta, and Omicron variants of SARS-CoV-2.

RESULTS

Our study included 280 records obtained from 147 household studies, contact tracing studies, or studies where epidemiological links were known. With each emerging variant, we found a progressive shortening of each of the analyzed key time-to-event periods, although we did not find statistically significant differences between the Omicron subvariants. We found that Omicron BA.1 had the shortest pooled estimates for the incubation period (3.49 days, 95% CI: 3.13-4.86 days), Omicron BA.5 for the serial interval (2.37 days, 95% CI: 1.71-3.04 days), and Omicron BA.1 for the realized generation time (2.99 days, 95% CI: 2.48-3.49 days). Only one estimate for the intrinsic generation time was available for Omicron subvariants: 6.84 days (95% CrI: 5.72-8.60 days) for Omicron BA.1. The ancestral lineage had the highest pooled estimates for each investigated key time-to-event period. We also observed shorter pooled estimates for the serial interval compared to the incubation period across the virus lineages. When pooling the estimates across different virus lineages, we found considerable heterogeneities (I2 > 80%; I2 refers to the percentage of total variation across studies that is due to heterogeneity rather than chance), possibly resulting from heterogeneities between the different study populations (e.g., deployed interventions, social behavior, demographic characteristics).

CONCLUSIONS

Our study supports the importance of conducting contact tracing and epidemiological investigations to monitor changes in SARS-CoV-2 transmission patterns. Our findings highlight a progressive shortening of the incubation period, serial interval, and generation time, which can lead to epidemics that spread faster, with larger peak incidence, and harder to control. We also consistently found a shorter serial interval than incubation period, suggesting that a key feature of SARS-CoV-2 is the potential for pre-symptomatic transmission. These observations are instrumental to plan for future COVID-19 waves.

Impact of COVID-19 on the treatment of depressive patients in Germany-a gap in care for the mentally ill?

Background

The COVID-19 pandemic led to a higher incidence of depression and a worsening of psychiatric conditions, while pre-existing constraints of the healthcare system and safety regulations limited psychiatric care.

Aims

We investigated the impact of the pandemic on the clinical care of patients with a single episode (SE-MDD) or major depressive disorder (MDD) in Germany.

Methods

Nationwide inpatient data were extracted from the German Institute for Hospital Remuneration System for 2020 and 2021 (depression data) and the Robert Koch Institute (COVID-19 incidence). Changes in inpatients were tested with linear regression models. Local cases of depression in our department compared to 2019 were explored with one-way ANOVA and Dunnett's test.

Results

Across Germany, the inpatient numbers with both SE-MDD and MDD declined by more than 50% during three out of four COVID-19 waves. Higher COVID-19 incidence correlated with decreased inpatient numbers. In our department, fewer MDD inpatients were treated in 2020 (adj. p < 0.001) and 2021 (adj. p < 0.001) compared to 2019, while the number of SE-MDD inpatients remained stable. During this period fewer elective and more emergency inpatients were admitted. In parallel, MDD outpatient admissions increased in 2021 compared to 2019 (adj. p = 0.002) and 2020 (adj. p = 0.003).

Conclusion

During high COVID-19 infection rates, MDD patients received less inpatient care, which might cause poor outcomes in the near future. These data highlight the necessity for improved infrastructure in the in- and outpatient domains to facilitate accessibility to adequate care.

Kidney outcome after mild to moderate COVID-19

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has a remarkable kidney tropism. While kidney effects are common in severe coronavirus disease 2019 (COVID-19), data on non-severe courses are limited. Here we provide a multilevel analysis of kidney outcomes after non-severe COVID-19 to test for eventual kidney sequela.

METHODS

This cross-sectional study investigates individuals after COVID-19 and matched controls recruited from the Hamburg City Health Study (HCHS) and its COVID-19 program. The HCHS is a prospective population-based cohort study within the city of Hamburg, Germany. During the COVID-19 pandemic the study additionally recruited subjects after polymerase chain reaction-confirmed SARS-CoV-2 infections. Matching was performed by age, sex and education. Main outcomes were estimated glomerular filtration rate (eGFR), albuminuria, Dickkopf3, haematuria and pyuria.

RESULTS

A total of 443 subjects in a median of 9 months after non-severe COVID-19 were compared with 1328 non-COVID-19 subjects. The mean eGFR was mildly lower in post-COVID-19 than non-COVID-19 subjects, even after adjusting for known risk factors {β = -1.84 [95% confidence interval (CI) -3.16 to -0.52]}. However, chronic kidney disease [odds ratio (OR) 0.90 (95% CI 0.48-1.66)] or severely increased albuminuria [OR 0.76 (95% CI 0.49-1.09)] equally occurred in post-COVID-19 and non-COVID-19 subjects. Haematuria, pyuria and proteinuria were also similar between the two cohorts, suggesting no ongoing kidney injury after non-severe COVID-19. Further, Dickkopf3 was not increased in the post-COVID-19 cohort, indicating no systematic risk for ongoing GFR decline [β = -72.19 (95% CI -130.0 to -14.4)].

CONCLUSION

While mean eGFR was slightly lower in subjects after non-severe COVID-19, there was no evidence for ongoing or progressive kidney sequela.

Delay-differential SEIR modeling for improved modelling of infection dynamics

SEIR (Susceptible-Exposed-Infected-Recovered) approach is a classic modeling method that is frequently used to study infectious diseases. However, in the vast majority of such models transitions from one population group to another are described using the mass-action law. That causes inability to reproduce observable dynamics of an infection such as the incubation period or progression of the disease's symptoms. In this paper, we propose a new approach to simulate the epidemic dynamics based on a system of differential equations with time delays and instant transitions to approximate durations of transition processes more correctly and make model parameters more clear. The suggested approach can be applied not only to Covid-19 but also to the study of other infectious diseases. We utilized it in the development of the delay-based model of the COVID-19 pandemic in Germany and France. The model takes into account testing of different population groups, symptoms progression from mild to critical, vaccination, duration of protective immunity and new virus strains. The stringency index was used as a generalized characteristic of the non-pharmaceutical government interventions in corresponding countries to contain the virus spread. The parameter identifiability analysis demonstrated that the presented modeling approach enables to significantly reduce the number of parameters and make them more identifiable. Both models are publicly available.

A data-driven Markov process for infectious disease transmission

The 2019 coronavirus pandemic exudes public health and socio-economic burden globally, raising an unprecedented concern for infectious diseases. Thus, describing the infectious disease transmission process to design effective intervention measures and restrict its spread is a critical scientific issue. We propose a level-dependent Markov model with infinite state space to characterize viral disorders like COVID-19. The levels and states in this model represent the stages of outbreak development and the possible number of infectious disease patients. The transfer of states between levels reflects the explosive transmission process of infectious disease. A simulation method with heterogeneous infection is proposed to solve the model rapidly. After that, simulation experiments were conducted using MATLAB according to the reported data on COVID-19 published by Johns Hopkins. Comparing the simulation results with the actual situation shows that our proposed model can well capture the transmission dynamics of infectious diseases with and without imposed interventions and evaluate the effectiveness of intervention strategies. Further, the influence of model parameters on transmission dynamics is analyzed, which helps to develop reasonable intervention strategies. The proposed approach extends the theoretical study of mathematical modeling of infectious diseases and contributes to developing models that can describe an infinite number of infected persons.

Risk factors for transmission in a COVID-19 cluster infection in a high school in the Republic of Korea

BACKGROUND

This study aimed to examine the scale, characteristics, risk factors, and modes of transmission in a coronavirus disease 2019 (COVID-19) outbreak at a high school in Seoul, Republic of Korea.

METHODS

An epidemiological survey was conducted of 1,118 confirmed cases and close contacts from a COVID-19 outbreak at an educational facility starting on May 31, 2021. In-depth interviews, online questionnaires, flow evaluations, and CCTV analyses were used to devise infection prevention measures. Behavioral and spatial risk factors were identified, and statistical significance was tested.

RESULTS

Among 3rd-year students, there were 33 confirmed COVID-19 cases (9.6%). Students who used a study room in the annex building showed a statistically significant 4.3-fold elevation in their relative risk for infection compared to those who did not use the study room. Moreover, CCTV facial recognition analysis confirmed that 17.8% of 3rd-year students did not wear masks and had the lowest percentage of mask-wearers by grade. The air epidemiological survey conducted in the study room in the annex, which met the 3 criteria for a closed space, confirmed that there was only 10% natural ventilation due to the poor ventilation system.

CONCLUSION

To prevent and manage the spread of COVID-19 in educational facilities, advance measures that consider the size, operation, and resources of each school are crucial. In addition, various survey methodologies should be used in future studies to quickly analyze a wider range of data that can inform an evidence-based quarantine response.

Spatio-Temporal Patterns of the SARS-CoV-2 Epidemic in Germany

Results from an explorative study revealing spatio-temporal patterns of the SARS-CoV-2/ COVID-19 epidemic in Germany are presented. We dispense with contestable model assumptions and show the intrinsic spatio-temporal patterns of the epidemic dynamics. The analysis is based on COVID-19 incidence data, which are age-stratified and spatially resolved at the county level, provided by the Federal Government's Public Health Institute of Germany (RKI) for public use. Although the 400 county-related incidence time series shows enormous heterogeneity, both with respect to temporal features as well as spatial distributions, the counties' incidence curves organise into well-distinguished clusters that coincide with East and West Germany. The analysis is based on dimensionality reduction, multidimensional scaling, network analysis, and diversity measures. Dynamical changes are captured by means of difference-in-difference methods, which are related to fold changes of the effective reproduction numbers. The age-related dynamical patterns suggest a considerably stronger impact of children, adolescents and seniors on the epidemic activity than previously expected. Besides these concrete interpretations, the work mainly aims at providing an atlas for spatio-temporal patterns of the epidemic, which serves as a basis to be further explored with the expertise of different disciplines, particularly sociology and policy makers. The study should also be understood as a methodological contribution to getting a handle on the unusual complexity of the COVID-19 pandemic.

Diabetes Mellitus and Its Association with Adverse In-Hospital Outcomes in Patients with COVID-19-A Nationwide Study

BACKGROUND

Diabetes mellitus (DM) represents a relevant risk factor regarding morbidity and mortality worldwide. However, only limited data exist regarding the impact of DM on the clinical outcome of patients with COVID-19 infection.

METHODS

All hospitalized patients with confirmed COVID-19-infection (ICD-code U07.1) during the year 2020 in Germany were included in the present study. Patients were stratified regarding the co-prevalence of DM (ICD-codes E10-E14), and the impact of DM on in-hospital case fatality and in-hospital adverse events was analyzed.

RESULTS

Overall, 176,137 hospitalizations with confirmed COVID-19 infection were documented; of these, 45,232 (25.7%) patients had an additional diagnosis of DM. Diabetic patients with COVID-19 were more often of male sex and 7 years older (median 76.0 (IQR: 66.0-83.0) vs. 69.0 (52.0-81.0) years, p < 0.001). COVID-19 patients with DM demonstrated an aggravated comorbidity profile, as reflected by a higher Charlson comorbidity index (6.0 (IQR: 4.0-8.0) vs. 3.0 (1.0-5.0), p < 0.001). Risk for pneumonia (OR 1.38 (95% CI: 1.35-1.41), p < 0.001), acute respiratory distress syndrome (OR 1.53 (95% CI: 1.47-1.60), p < 0.001), and need for intensive care (21.3% vs. 13.3%, p < 0.001) were increased in DM patients. DM was an independent risk factor for acute kidney failure (OR 1.49 (95% CI: 1.44-1.53), p < 0.001), dialysis (OR 1.56 (95% CI: 1.47-1.66), p < 0.001), mechanical ventilation (OR: 1.49 (95% CI: 1.43-1.56), p < 0.001), extracorporeal membrane oxygenation (OR 1.44 (95% CI: 1.27-1.62), p < 0.001), major adverse cardiac and cerebrovascular events (OR: 1.24 (95% CI: 1.20-1.27), p < 0.001), and in-hospital mortality (OR: 1.26 (95% CI: 1.22-1.30), p < 0.001).

CONCLUSIONS

In patients with COVID-19-infection, DM is a relevant risk factor for adverse events, including mortality. The vulnerable patient group of diabetics with COVID-19 requires intense medical care and monitoring during hospitalization.

Dynamics-informed deconvolutional neural networks for super-resolution identification of regime changes in epidemiological time series

The ability to infer the timing and amplitude of perturbations in epidemiological systems from their stochastically spread low-resolution outcomes is crucial for multiple applications. However, the general problem of connecting epidemiological curves with the underlying incidence lacks the highly effective methodology present in other inverse problems, such as super-resolution and dehazing from computer vision. Here, we develop an unsupervised physics-informed convolutional neural network approach in reverse to connect death records with incidence that allows the identification of regime changes at single-day resolution. Applied to COVID-19 data with proper regularization and model-selection criteria, the approach can identify the implementation and removal of lockdowns and other nonpharmaceutical interventions (NPIs) with 0.93-day accuracy over the time span of a year.

[Occupational medical aspects of COVID-19 pandemic containment: experiences from a large chemical company]

INTRODUCTION

With the present paper we aim to describe the experience of a large chemical company in tackling the COVID-19 pandemic. Specifically, we describe the timing and content of implemented measures and outline the course of the pandemic from the company's perspective.

METHODS

We describe the infection protection measures and the pandemic course at the company's main site in Ludwigshafen (Germany) from March 2020 to May 2022. Company-specific data on the date of reporting an infection, suspected place of infection, number of close contacts, and the employee group were used to calculate 7-day-incidences and visualized, among other things, by means of a plant map (active infections) and a network chart (chains of infection). In addition, a weighted average of the incidences from districts close to the plant (weighted by the number of resident employees within the district) was calculated using publicly available data by the Robert Koch Institute and compared with the course of company-specific incidences.

RESULTS

At the end of follow-up on 31^st May 2022, 9,379 infections with SARS-CoV-2 had been recorded in employees and 758 more in leasing staff, including 368 (4%) and 84 (11%) suspected infections at the workplace/on-site, respectively. The course of 7-day incidences among employees was mainly consistent with that in the surrounding districts. The incidence of suspected infections on-site/at the workplace remained predominantly at a comparatively low level below 100 new infections over 7 days/100,000.

DISCUSSION

The continuous monitoring and analysis of new SARS-CoV-2 cases among employees provides valuable information for the effective management of protective measures in the company. It enables a targeted response to changes in the number of new cases on the plant site by tightening or relaxing protective measures.

Former SARS-CoV-2 Infection Was Related to Decreased VO2 Peak and Exercise Hypertension in Athletes

The impact of former COVID-19 infection on the performance of athletes is not fully understood. We aimed to identify differences in athletes with and without former COVID-19 infections. Competitive athletes who presented for preparticipation screening between April 2020 and October 2021 were included in this study, stratified for former COVID-19 infection, and compared. Overall, 1200 athletes (mean age 21.9 ± 11.6 years; 34.3% females) were included in this study from April 2020 to October 2021. Among these, 158 (13.1%) athletes previously had COVID-19 infection. Athletes with COVID-19 infection were older (23.4 ± 7.1 vs. 21.7 ± 12.1 years, p < 0.001) and more often of male sex (87.7% vs. 64.0%, p < 0.001). While systolic/diastolic blood pressure at rest was comparable between both groups, maximum systolic (190.0 [170.0/210.0] vs. 180.0 [160.0/205.0] mmHg, p = 0.007) and diastolic blood pressure (70.0 [65.0/75.0] vs. 70.0 [60.0/75.0] mmHg, p = 0.012) during the exercise test and frequency of exercise hypertension (54.2% vs. 37.8%, p < 0.001) were higher in athletes with COVID-19 infection. While former COVID-19 infection was not independently associated with higher blood pressure at rest and maximum blood pressure during exercise, former COVID-19 infection was related to exercise hypertension (OR 2.13 [95%CI 1.39-3.28], p < 0.001). VO₂ peak was lower in athletes with compared to those without COVID-19 infection (43.4 [38.3/48.0] vs. 45.3 [39.1/50.6] mL/min/kg, p = 0.010). SARS-CoV-2 infection affected VO₂ peak negatively (OR 0.94 [95%CI 0.91-0.97], p < 0.0019). In conclusion, former COVID-19 infection in athletes was accompanied by a higher frequency of exercise hypertension and reduced VO₂ peak.

Total escape of SARS-CoV-2 from dual monoclonal antibody therapy in an immunocompromised patient

Monoclonal antibodies (mAbs) directed against the spike of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are effective therapeutic options to combat infections in high-risk patients. Here, we report the adaptation of SARS-CoV-2 to the mAb cocktail REGN-COV in a kidney transplant patient with hypogammaglobulinemia. Following mAb treatment, the patient did not clear the infection. During viral persistence, SARS-CoV-2 acquired three novel spike mutations. Neutralization and mouse protection analyses demonstrate a complete viral escape from REGN-COV at the expense of ACE-2 binding. Final clearance of the virus occurred upon reduction of the immunosuppressive regimen and total IgG substitution. Serology suggests that the development of highly neutralizing IgM rather than IgG substitution aids clearance. Our findings emphasise that selection pressure by mAbs on SARS-CoV-2 can lead to development of escape variants in immunocompromised patients. Thus, modification of immunosuppressive therapy, if possible, might be preferable to control and clearance of the viral infection.

Monitoring the SARS-CoV-2 Pandemic: Prevalence of Antibodies in a Large, Repetitive Cross-Sectional Study of Blood Donors in Germany—Results from the SeBluCo Study 2020–2022

SARS-CoV-2 serosurveillance is important to adapt infection control measures and estimate the degree of underreporting. Blood donor samples can be used as a proxy for the healthy adult population. In a repeated cross-sectional study from April 2020 to April 2021, September 2021, and April/May 2022, 13 blood establishments collected 134,510 anonymised specimens from blood donors in 28 study regions across Germany. These were tested for antibodies against the SARS-CoV-2 spike protein and nucleocapsid, including neutralising capacity. Seroprevalence was adjusted for test performance and sampling and weighted for demographic differences between the sample and the general population. Seroprevalence estimates were compared to notified COVID-19 cases. The overall adjusted SARS-CoV-2 seroprevalence remained below 2% until December 2020 and increased to 18.1% in April 2021, 89.4% in September 2021, and to 100% in April/May 2022. Neutralising capacity was found in 74% of all positive specimens until April 2021 and in 98% in April/May 2022. Our serosurveillance allowed for repeated estimations of underreporting from the early stage of the pandemic onwards. Underreporting ranged between factors 5.1 and 1.1 in the first two waves of the pandemic and remained well below 2 afterwards, indicating an adequate test strategy and notification system in Germany.

High variability of COVID-19 case fatality rate in Germany

BACKGROUND

During the first wave of the COVID-19 pandemic a high case fatality rate (CFR) was noticed worldwide including also Germany where the first European cases have been observed. The WHO recommended immediate intubation for patients with dyspnoea which has since been revised after reviewing the initial clinical outcome. The objective of this study is to analyze CFR and assess if there is an advantage of a more conservative management of COVID-19 induced hypoxemia.

METHODS

PCR confirmed COVID-19 infections and death counts were obtained for all German districts from 27 Jan 2020 until 15 Feb 2021 using official reports of Robert Koch Institute Berlin, Germany. A moving average CFRt was constructed by dividing disease related deaths two weeks after a given index day by the number of infections two weeks prior to that date. In addition to a local comparison also mortality outcomes in other German speaking countries were compared.

RESULTS

The mean CFR is estimated to be 2.92% based on 71.965 fatalities and 2.465.407 cases. There was a large regional scattering of CFRs across the German districts. Differences of the mortality pattern were observed also at state level and preserved across different sex and age groups while being largely independent of case numbers. Although Munich city had higher infection rates, more patients died during the first wave in Hamburg (OR 1.6, 95% CI 1.3-1.9) which was mirrored also by higher death risk at Hamburg intensive care units (OR 2.0, 95% CI 1.3-3.1). While the majority of Munich hospitals favoured a conservative management of hypoxemia including high flow nasal cannula (HFNC), Hamburg hospitals followed a more aggressive scheme of early mechanical ventilation (MV). Austria and Switzerland experienced higher CFRs than Germany during the first wave but after changing their treatment guidelines, both countries experienced lower CFRs during the second wave.

CONCLUSION

Using retrospective public health data, different case fatality rates have been observed across Germany. A more conservative management of COVID-19 induced Adult Respiratory Distress Syndrome (ARDS) is justified also by epidemiological data.

Patient characteristics and testing over COVID-19 waves 1 and 2 from the first German COVID-19 testing unit in Munich, Germany

BACKGROUND

In Munich, the first German case of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was detected on 27 January 2020 at the Division of Infectious Diseases and Tropical Medicine of the University Hospital LMU Munich (DIDTM), and consecutively the Covid Testing Unit was established. Germany advocated several public health measures to control the outbreak. This study investigates the effects of measures on health service utilization in the public, which in turn can alter case numbers and test positivity rates.

METHOD

Our retrospective observational study was conducted to determine the effects of public health measures on the utilization of a testing facility and positivity rates from the first operational COVID-19 testing facility in Munich for waves 1 and 2 over a period of 14 months. This was accomplished by comparing trends in client characteristics including age, gender, symptoms, and socio-demographic aspects over time to non-pharmaceutical measures in Germany. To depict trend changes in testing numbers over time, we developed a negative binomial model with multiple breakpoints.

RESULTS

In total 9861 tests were conducted on 6989 clients. The clients were mostly young (median age: 34), female (60.58%), and asymptomatic (67.89%). Among those who tested positive for SARS-CoV-2, 67.72% were symptomatic while the percentage was 29.06% among those who tested negative. There are other risk factors, but a SARS-CoV-2-positive colleague at work is the most prominent factor. Trend changes in the clients' testing numbers could be attributed to the implementation of various public health measures, testing strategies, and attitudes of individuals toward the pandemic. However, test positivity rates did not change substantially during the second wave of the pandemic.

CONCLUSION

We could show that implementation or changes in public health measures have a strong effect on the utilization of testing facilities by the general public, which independently of the true epidemiological background situation can result in changing test numbers.

Does 2x2 airplane passenger contact tracing for infectious respiratory pathogens work? A systematic review of the evidence

We critically appraised the literature regarding in-flight transmission of a range of respiratory infections to provide an evidence base for public health policies for contact tracing passengers, given the limited pathogen-specific data for SARS-CoV-2 currently available. Using PubMed, Web of Science, and other databases including preprints, we systematically reviewed evidence of in-flight transmission of infectious respiratory illnesses. A meta-analysis was conducted where total numbers of persons on board a specific flight was known, to calculate a pooled Attack Rate (AR) for a range of pathogens. The quality of the evidence provided was assessed using a bias assessment tool developed for in-flight transmission investigations of influenza which was modelled on the PRISMA statement and the Newcastle-Ottawa scale. We identified 103 publications detailing 165 flight investigations. Overall, 43.7% (72/165) of investigations provided evidence for in-flight transmission. H1N1 influenza A virus had the highest reported pooled attack rate per 100 persons (AR = 1.17), followed by SARS-CoV-2 (AR = 0.54) and SARS-CoV (AR = 0.32), Mycobacterium tuberculosis (TB, AR = 0.25), and measles virus (AR = 0.09). There was high heterogeneity in estimates between studies, except for TB. Of the 72 investigations that provided evidence for in-flight transmission, 27 investigations were assessed as having a high level of evidence, 23 as medium, and 22 as low. One third of the investigations that reported on proximity of cases showed transmission occurring beyond the 2x2 seating area. We suggest that for emerging pathogens, in the absence of pathogen-specific evidence, the 2x2 system should not be used for contact tracing. Instead, alternate contact tracing protocols and close contact definitions for enclosed areas, such as the same cabin on an aircraft or other forms of transport, should be considered as part of a whole of journey approach.

Molecular characterisation and tracking of severe acute respiratory syndrome coronavirus 2 in Thailand, 2020-2022

The global COVID-19 pandemic, caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was first detected in China in December 2019. To date, there have been approximately 3.4 million reported cases of COVID-19 and over 24,000 deaths in Thailand. In this study, we investigated the molecular characteristics and evolution of SARS-CoV-2 in Thailand from 2020 to 2022. Two hundred sixty-eight SARS-CoV-2 isolates, collected mostly in Bangkok from COVID-19 patients, were characterised by partial genome sequencing. Moreover, the viruses in 5,627 positive SARS-CoV-2 samples were identified as viral variants - B.1.1.7 (Alpha), B.1.617.2 (Delta), B.1.1.529 (Omicron/BA.1), or B.1.1.529 (Omicron/BA.2) - by multiplex real-time reverse transcription polymerase chain reaction (RT-PCR) assays. The results revealed that B.1.36.16 caused the predominant outbreak in the second wave (December 2020-January 2021), B.1.1.7 (Alpha) in the third wave (April-June 2021), B.1.617.2 (Delta) in the fourth wave (July-December 2021), and B.1.1.529 (Omicron) in the fifth wave (January-March 2022). The evolutionary rate of the viral genome was 2.60 × 10^-3 (95% highest posterior density [HPD], 1.72 × 10^-3 to 3.62 × 10^-3) nucleotide substitutions per site per year. Continued molecular surveillance of SARS-CoV-2 is crucial for monitoring emerging variants with the potential to cause new COVID-19 outbreaks.

Intensity and lag-time of non-pharmaceutical interventions on COVID-19 dynamics in German hospitals

Introduction

Evaluating the potential effects of non-pharmaceutical interventions on COVID-19 dynamics is challenging and controversially discussed in the literature. The reasons are manifold, and some of them are as follows. First, interventions are strongly correlated, making a specific contribution difficult to disentangle; second, time trends (including SARS-CoV-2 variants, vaccination coverage and seasonality) influence the potential effects; third, interventions influence the different populations and dynamics with a time delay.

Methods

In this article, we apply a distributed lag linear model on COVID-19 data from Germany from January 2020 to June 2022 to study intensity and lag time effects on the number of hospital patients and the number of prevalent intensive care patients diagnosed with polymerase chain reaction tests. We further discuss how the findings depend on the complexity of accounting for the seasonal trends.

Results and discussion

Our findings show that the first reducing effect of non-pharmaceutical interventions on the number of prevalent intensive care patients before vaccination can be expected not before a time lag of 5 days; the main effect is after a time lag of 10-15 days. In general, we denote that the number of hospital and prevalent intensive care patients decrease with an increase in the overall non-pharmaceutical interventions intensity with a time lag of 9 and 10 days. Finally, we emphasize a clear interpretation of the findings noting that a causal conclusion is challenging due to the lack of a suitable experimental study design.

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.

Association Between Population-Level Factors and Household Secondary Attack Rate of SARS-CoV-2: A Systematic Review and Meta-analysis

Background

Accurate estimation of household secondary attack rate (SAR) is crucial to understand the transmissibility of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The impact of population-level factors, such as transmission intensity in the community, on SAR estimates is rarely explored.

Methods

In this study, we included articles with original data to compute the household SAR. To determine the impact of transmission intensity in the community on household SAR estimates, we explored the association between SAR estimates and the incidence rate of cases by country during the study period.

Results

We identified 163 studies to extract data on SARs from 326 031 cases and 2 009 859 household contacts. The correlation between the incidence rate of cases during the study period and SAR estimates was 0.37 (95% CI, 0.24-0.49). We found that doubling the incidence rate of cases during the study period was associated with a 1.2% (95% CI, 0.5%-1.8%) higher household SAR.

Conclusions

Our findings suggest that the incidence rate of cases during the study period is associated with higher SAR. Ignoring this factor may overestimate SARs, especially for regions with high incidences, which further impacts control policies and epidemiological characterization of emerging variants.

COVID-19 in one region of New Zealand: a descriptive epidemiological study

OBJECTIVE

To describe the epidemiology of COVID-19 in one region of New Zealand in the context of the national lockdown and provide a reference for comparing infection dynamics and control measures between SARS-Cov-2 strains.  Methods: Epidemiological linking and analysis of COVID-19 cases and their close contacts residing in the geographical area served by the Southern District Health Board (SDHB).  Results: From 13 March to 5 April 5 2020, 186 cases were laboratory-confirmed with wild-type Sars-Cov-2 in SDHB. Overall, 35·1% of cases were attributable to household transmission, 27·0% to non-household, 25·4% to overseas travel and 12·4% had no known epidemiological links. The highest secondary attack rate was observed in households during lockdown (15·3%, 95%CI 10·4-21·5). The mean serial interval in 50 exclusive infector-infectee pairs was 4·0 days (95%CI 3·2-4·7days), and the mean incubation period was 3.4 days (95%CI 2·7-4·2).

CONCLUSIONS

The SARS-CoV-2 incubation period may be shorter than early estimates that were limited by uncertainties in exposure history or small sample sizes.

IMPLICATIONS FOR PUBLIC HEALTH

The continuation of household transmission during lockdown highlights the need for effective home-based quarantine guidance. Our findings of a short incubation period highlight the need to contact trace and isolate as rapidly as possible.

Delta and Omicron: protective measures and SARS-CoV-2 infections in day care centres in Germany in the 4th and 5th wave of the pandemic 2021/2022

Background

During the five waves of the SARS-CoV-2 pandemic so far, German early childhood education and care (ECEC) centres implemented various protective measures, such as wearing a face mask, fixed children-staff groups or regular ventilation. In addition, parents and ECEC staff were increasingly vaccinated throughout 2021. During the 4th wave, variant of concern (VOC) Delta-driven transmission indicators reached record values at the end of 2021. Those values were even exceeded in the 5th wave at the beginning of 2022 when Omicron dominated. We examine which factors facilitated or prevented infection with SARS-CoV-2 in ECEC centres, and if these differed between different phases within wave 4 (Delta) and 5 (Omicron).

Methods

Since August 2020, a weekly online survey among approximately 8000 ECEC managers has been conducted, monitoring both incident SARS-CoV-2 infections and protective measures taken. We included data from calendar week 26/2021 to 05/2022. We estimate the probability of any infections and the number of SARS-CoV-2 infections in children, parents and staff using random-effect-within-between (REWB) panel models for binomial and count data.

Results

While children, parents and staff of ECEC centres with a high proportion of children from families with low socioeconomic status (SES) have a higher risk of infections in the beginning of wave 4 (OR up to 1.99 [1.56; 2.56]), this effect diminishes for children and parents with rising incidences. Protective measures, such as wearing face masks, tend to have more extensive effects with rising incidences in wave 5 (IRR up to 0.87 [0.8; 0.93]). Further, the protective effect of vaccination against infection among staff is decreasing from wave 4 to wave 5 (OR 0.3 [0.16; 0.55] to OR 0.95, [0.84; 1.07, n.s.]). The degree of transmission from staff to child and from staff to parent is decreasing from wave 4 to wave 5, while transmission from child to staff seems to increase.

Conclusion

While Omicron seems to affect children and parents from ECEC centres with families with all SES levels more equally than Delta, the protective effect of vaccination against infection is decreasing and the effect of protective measures like face masks becomes increasingly important. In order to prevent massive closures of ECEC centres due to infection of staff, protective measures should be strictly adhered to, especially to protect staff in centres with a high proportion of children from families with low socioeconomic status.

Case Fatality of Hospitalized Patients with COVID-19 Infection Suffering from Acute Respiratory Distress Syndrome in Germany

Aims: Patients suffering from viral pneumonia caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are at risk of developing acute respiratory distress syndrome (ARDS). ARDS is a serious complication of COVID-19 that requires early recognition and comprehensive management. Little is known about the concomitant prevalence of both entities in Germany. Thus, we sought to analyze predictors and regional trends of case fatality in patients with COVID-19 and ARDS in Germany. Methods: We analyzed data on the characteristics, comorbidities and in-hospital outcomes for all hospitalized patients with COVID-19 and compared those with and without ARDS in Germany in 2020. Results: Overall, 176,137 hospitalized patients with confirmed COVID-19 were included in this analysis; among these, 11,594 (6.6%) suffered from ARDS. Most patients with ARDS were treated in hospitals in urban areas (n = 6485); proportion rate of mechanical ventilation was higher (45.9%) compared to those treated in hospitals of suburban (36.1%) or rural areas (32.0%). Proportion of ARDS grew exponentially with age until the sixth decade of life. Case-fatality rate was considerably higher in COVID-19 patients with ARDS compared to those without (48.3% vs. 15.8%; p < 0.001). Independent predictors of in-hospital case fatality with an OR > 3 were age ≥ 70 years, severe ARDS, severe liver disease, acute renal failure, stroke, dialysis treatment, shock and necessity of ECMO. Conclusions: The case fatality of COVID-19 patients with ARDS is dramatically high and shows relevant regional disparities. Our findings may help to draw more attention to predictors for in-hospital case fatality in patients hospitalized with COVID-19 and suffering from ARDS.

A novel method to monitor COVID-19 fatality rate in real-time, a key metric to guide public health policy

An accurate estimator of the real-time fatality rate is warranted to monitor the progress of ongoing epidemics, hence facilitating the policy-making process. However, most of the existing estimators fail to capture the time-varying nature of the fatality rate and are often biased in practice. A simple real-time fatality rate estimator with adjustment for reporting delays is proposed in this paper using the fused lasso technique. This approach is easy to use and can be broadly applied to public health practice as only basic epidemiological data are required. A large-scale simulation study suggests that the proposed estimator is a reliable benchmark for formulating public health policies during an epidemic with high accuracy and sensitivity in capturing the changes in the fatality rate over time, while the other two commonly-used case fatality rate estimators may convey delayed or even misleading signals of the true situation. The application to the COVID-19 data in Germany between January 2020 and January 2022 demonstrates the importance of the social restrictions in the early phase of the pandemic when vaccines were not available, and the beneficial effects of vaccination in suppressing the fatality rate to a low level since August 2021 irrespective of the rebound in infections driven by the more infectious Delta and Omicron variants during the fourth wave.

Temporal Trends in Patients with Peripheral Artery Disease Influenced by COVID-19 Pandemic

Background: The COVID-19 pandemic influences the health care management of acute and chronic diseases. Data concerning the influence of the pandemic on hospitalizations of patients with peripheral artery disease (PAD) are sparse. Methods: We analysed all patients hospitalized due to PAD between 1 January 2019 and 31 December 2020 in Germany. Hospitalizations of PAD patients during the pre-pandemic year 2019 were compared to the pandemic year 2020. Results: Overall, 361,029 hospitalizations of PAD patients in the years 2019 and 2020 (55.4% aged ≥70 years; 36.6% females) were included in this study. In the pre-pandemic year of 2019, a total of 25,501 (13.2%) more hospitalizations due to PAD were detected compared to the COVID-19 pandemic year of 2020 (2019: 192,765 [53.4%] vs. 2020: 168,264 [46.6%], p = 0.065). Overall, in 610 (0.4%) of the hospitalization cases, a COVID-19 infection was diagnosed. Regarding interventional/surgical treatments, total numbers of peripheral endovascular intervention of the lower extremity decreased by 9.9% (83,845 vs. 75,519, p < 0.001), surgical peripheral artery revascularization of the lower extremity by 11.4% (32,447 vs. 28,754, p = 0.041) and amputations by 4.0% (20,612 vs. 19,784, p < 0.001) in 2020 compared to 2019. The case fatality rate (2.6% vs. 2.4%, p < 0.001), as well as MACCE rate (3.4% vs. 3.2%, p < 0.001), were slightly higher during the pandemic year 2020 compared to the pre-pandemic year 2019. Conclusions: The COVID-19 pandemic influenced the number of hospitalizations of PAD patients with a 13.2% reduction in hospital admissions and decreased total numbers of revascularization and amputation treatments.

Blockchain solution benefits for controlling pandemics: Bottom-up decentralization, automation with real-time update, and immutability with privacy preservation

The current COVID-19 pandemic has created turmoil around the world. To fight this ongoing global crisis and future ones, all stakeholders must collaborate and share timely and truthful information. This paper proposes a blockchain solution based on its inherent technological advantages. We posit that benefits can be derived from three unique blockchain features: bottom-up decentralization, automation with real-time update, and immutability with privacy preservation. A decentralized common platform provides easy access and increases participation in disease surveillance, which reduces the estimation errors of the compartmental model parameters. Automation with real-time update facilitates prompt detection and diagnosis, accurate contact tracing, and targeted mitigation and containment, achieving faster recovery and slower transmission. Being immutable while preserving privacy, the blockchain solution enhances respondents' willingness to truthfully report their contact history, avoiding false and erroneous data that will cause wrong estimates on pandemic transmission and recovery. Thus, the blockchain solution mitigates three types of risks: sample variance, delay, and bias. Through simulation, we quantify the value of the blockchain solution in these three aspects. Accordingly, we provide specific action plans based on our research findings: before building blockchain solutions for controlling COVID-19, governments and organizations can calculate the blockchain benefits and decide whether or not they should invest in such blockchain solutions by conducting a cost-benefit analysis.

Phylogenetic and phylodynamic approaches to understanding and combating the early SARS-CoV-2 pandemic

Determining the transmissibility, prevalence and patterns of movement of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections is central to our understanding of the impact of the pandemic and to the design of effective control strategies. Phylogenies (evolutionary trees) have provided key insights into the international spread of SARS-CoV-2 and enabled investigation of individual outbreaks and transmission chains in specific settings. Phylodynamic approaches combine evolutionary, demographic and epidemiological concepts and have helped track virus genetic changes, identify emerging variants and inform public health strategy. Here, we review and synthesize studies that illustrate how phylogenetic and phylodynamic techniques were applied during the first year of the pandemic, and summarize their contributions to our understanding of SARS-CoV-2 transmission and control.

Importance of external quality assessment for SARS-CoV-2 antigen detection during the COVID-19 pandemic

Background: Antigen testing has become an essential part of fighting the ongoing COVID-19 pandemic. With the continual increase in available tests, independent and extensive comparative evaluations using data from external quality assessment (EQA) studies to evaluate test performance between different users are required.

Objectives: An EQA scheme was established to assess the sensitivity of antigen tests and the potential impact of circulating SARS-CoV-2 strains on their performance.

Study design: Panels were prepared for three challenges in 2021 containing inactivated SARS-CoV-2-positive samples of various genetic strains (including variants of concern, VOCs) at different concentrations, and negative samples. Data was analysed based on qualitative testing results in relation to the antigen test used.

Results: Participants registered for each individual challenge in any combination. In total, 258 respondents from 27 countries worldwide were counted submitting 472 datasets. All core samples were correctly reported by 76.7 to 83.1% at participant level and by 73.5 to 83.8% at dataset level. Sensitivity differences could be shown in viral loads and SARS-CoV-2 strains/variants including the impact on performance by a B.1.1.7-like mutant strain with a deletion in the nucleoprotein gene. Lateral flow rapid antigen tests showed a higher rate of false negatives in general compared with automated point-of-care tests and laboratory ELISA/immunoassays.

Conclusions: EQA schemes can provide valuable data to inform participants about weaknesses in their testing process or methods and support ongoing assay evaluations for regulatory approval or post-market surveillance.

Probiotics in the Management of Mental and Gastrointestinal Post-COVID Symptomes

Patients with “post-COVID” syndrome manifest with a variety of signs and symptoms that continue/develop after acute COVID-19. Among the most common are gastrointestinal (GI) and mental symptoms. The reason for symptom occurrence lies in the SARS-CoV-2 capability of binding to exact receptors, among other angiotensin converting enzyme 2 (ACE2) receptors in gastrointestinal lining and neuropilin-1 (NRP-1) in the nervous system, which leads to loss of gastrointestinal and blood-brain barriers integrity and function. The data are mounting that SARS-CoV-2 can trigger systemic inflammation and lead to disruption of gut-brain axis (GBA) and the development of disorders of gut brain interaction (DGBIs). Functional dyspepsia (FD) and irritable bowel syndrome (IBS) are the most common DGBIs syndromes. On the other hand, emotional disorders have also been demonstrated as DGBIs. Currently, there are no official recommendations or recommended procedures for the use of probiotics in patients with COVID-19. However, it can be assumed that many doctors, pharmacists, and patients will want to use a probiotic in the treatment of this disease. In such cases, strains with documented activity should be used. There is a constant need to plan and conduct new trials on the role of probiotics and verify their clinical efficacy for counteracting the negative consequences of COVID-19 pandemic. Quality control is another important but often neglected aspect in trials utilizing probiotics in various clinical entities. It determines the safety and efficacy of probiotics, which is of utmost importance in patients with post-acute COVID-19 syndrome.

Identifiability of parameters in mathematical models of SARS-CoV-2 infections in humans

Determining accurate estimates for the characteristics of the severe acute respiratory syndrome coronavirus 2 in the upper and lower respiratory tracts, by fitting mathematical models to data, is made difficult by the lack of measurements early in the infection. To determine the sensitivity of the parameter estimates to the noise in the data, we developed a novel two-patch within-host mathematical model that considered the infection of both respiratory tracts and assumed that the viral load in the lower respiratory tract decays in a density dependent manner and investigated its ability to match population level data. We proposed several approaches that can improve practical identifiability of parameters, including an optimal experimental approach, and found that availability of viral data early in the infection is of essence for improving the accuracy of the estimates. Our findings can be useful for designing interventions.

Impact of coronavirus disease (COVID-19) pandemic on physical activity of patients with cardiac implantable electronic devices—A remote monitoring study

Objectives

The study aims to investigate the impact of COVID-19 pandemic on physical activity and frequency of implantable cardioverter-defibrillator (ICD) therapies of patients with cardiac implantable electronic devices.

Methods and results

Physical activity, heart rate and ICD-therapies were assessed via routine remote monitoring over two years. We focussed on a 338-day period during COVID-19 pandemic that was divided in 6 time-intervals defined by public health interventions and compared to the previous regular year. Paired nonparametric longitudinal analysis was performed to detect differences between time-intervals. To model effects of age, sex and time we applied a nonparametric ANOVA-type-statistic. 147 patients with cardiac implantable electronic devices were analysed. Longitudinal analysis of physical activity in 2019 and 2020 showed a specific weekly and seasonal pattern. Physical activity was reduced during the pandemic (mean daily physical activity 2019: 12.4% vs. 2020: 11.5%; p<0.0001) with the strongest reductions (fold changes 0.885/0.889, p<0.0001/p<0.0001) during the two lockdown-periods. In older patients (>70 years), physical activity was decreased in every time-interval of the year 2020. In time-intervals of eased restrictions, physical activity of younger patients (≤70 years) was not different compared to 2019. No variation in mean heart rate, arrhythmia-burden and count of ICD-therapies was found.

Conclusion

Physical activity shows fluctuations dependent on days of the week and time of the year. During the pandemic, physical activity was reduced in patients with cardiac implantable electronic devices with the strongest reductions during lockdown-periods. Younger patients resumed former levels of physical activity in times of eased restrictions while older patients remained less active. Thus, activation of the elderly population is important to prevent long-term health impairments due to the pandemic.

Modelling of a triage scoring tool for SARS-COV-2 PCR testing in health-care workers: data from the first German COVID-19 Testing Unit in Munich

Background

Numerous scoring tools have been developed for assessing the probability of SARS-COV-2 test positivity, though few being suitable or adapted for outpatient triage of health care workers.

Methods

We retrospectively analysed 3069 patient records of health care workers admitted to the COVID-19 Testing Unit of the Ludwig-Maximilians-Universität of Munich between January 27 and September 30, 2020, for real-time polymerase chain reaction analysis of naso- or oropharyngeal swabs. Variables for a multivariable logistic regression model were collected from self-completed case report forms and selected through stepwise backward selection. Internal validation was conducted by bootstrapping. We then created a weighted point-scoring system from logistic regression coefficients.

Results

4076 (97.12%) negative and 121 (2.88%) positive test results were analysed. The majority were young (mean age: 38.0), female (69.8%) and asymptomatic (67.8%). Characteristics that correlated with PCR-positivity included close-contact professions (physicians, nurses, physiotherapists), flu-like symptoms (e.g., fever, rhinorrhoea, headache), abdominal symptoms (nausea/emesis, abdominal pain, diarrhoea), less days since symptom onset, and contact to a SARS-COV-2 positive index-case. Variables selected for the final model included symptoms (fever, cough, abdominal pain, anosmia/ageusia) and exposures (to SARS-COV-positive individuals and, specifically, to positive patients). Internal validation by bootstrapping yielded a corrected Area Under the Receiver Operating Characteristics Curve of 76.43%. We present sensitivity and specificity at different prediction cut-off points. In a subgroup with further workup, asthma seems to have a protective effect with regard to testing result positivity and measured temperature was found to be less predictive than anamnestic fever.

Conclusions

We consider low threshold testing for health care workers a valuable strategy for infection control and are able to provide an easily applicable triage score for the assessment of the probability of infection in health care workers in case of resource scarcity.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07627-5.

Vaccine-associated enhanced respiratory pathology in COVID-19 hamsters after TH2-biased immunization

Vaccine-associated enhanced respiratory disease (VAERD) is a severe complication for some respiratory infections. To investigate the potential for VAERD induction in coronavirus disease 2019 (COVID-19), we evaluate two vaccine leads utilizing a severe hamster infection model: a T helper type 1 (T_H1)-biased measles vaccine-derived candidate and a T_H2-biased alum-adjuvanted, non-stabilized spike protein. The measles virus (MeV)-derived vaccine protects the animals, but the protein lead induces VAERD, which can be alleviated by dexamethasone treatment. Bulk transcriptomic analysis reveals that our protein vaccine prepares enhanced host gene dysregulation in the lung, exclusively up-regulating mRNAs encoding the eosinophil attractant CCL-11, T_H2-driving interleukin (IL)-19, or T_H2 cytokines IL-4, IL-5, and IL-13. Single-cell RNA sequencing (scRNA-seq) identifies lung macrophages or lymphoid cells as sources, respectively. Our findings imply that VAERD is caused by the concerted action of hyperstimulated macrophages and T_H2 cytokine-secreting lymphoid cells and potentially links VAERD to antibody-dependent enhancement (ADE). In summary, we identify the cytokine drivers and cellular contributors that mediate VAERD after T_H2-biased vaccination.

Characterization of SARS-CoV-2 Escape Mutants to a Pair of Neutralizing Antibodies Targeting the RBD and the NTD

Mutations in the spike protein of SARS-CoV-2 can lead to evasion from neutralizing antibodies and affect the efficacy of passive and active immunization strategies. Immunization of mice harboring an entire set of human immunoglobulin variable region gene segments allowed to identify nine neutralizing monoclonal antibodies, which either belong to a cluster of clonally related RBD or NTD binding antibodies. To better understand the genetic barrier to emergence of SARS-CoV-2 variants resistant to these antibodies, escape mutants were selected in cell culture to one antibody from each cluster and a combination of the two antibodies. Three independently derived escape mutants to the RBD antibody harbored mutations in the RBD at the position T478 or S477. These mutations impaired the binding of the RBD antibodies to the spike protein and conferred resistance in a pseudotype neutralization assay. Although the binding of the NTD cluster antibodies were not affected by the RBD mutations, the RBD mutations also reduced the neutralization efficacy of the NTD cluster antibodies. The mutations found in the escape variants to the NTD antibody conferred resistance to the NTD, but not to the RBD cluster antibodies. A variant resistant to both antibodies was more difficult to select and only emerged after longer passages and higher inoculation volumes. VOC carrying the same mutations as the ones identified in the escape variants were also resistant to neutralization. This study further underlines the rapid emergence of escape mutants to neutralizing monoclonal antibodies in cell culture and indicates the need for thorough investigation of escape mutations to select the most potent combination of monoclonal antibodies for clinical use.

Asseri A, Binyamin SS, Al-Rabia MW. Enhanced Gravitational Search Optimization with Hybrid Deep Learning Model for COVID-19 Diagnosis on Epidemiology Data

Effective screening provides efficient and quick diagnoses of COVID-19 and could alleviate related problems in the health care system. A prediction model that combines multiple features to assess contamination risks was established in the hope of supporting healthcare workers worldwide in triaging patients, particularly in situations with limited health care resources. Furthermore, a lack of diagnosis kits and asymptomatic cases can lead to missed or delayed diagnoses, exposing visitors, medical staff, and patients to 2019-nCoV contamination. Non-clinical techniques including data mining, expert systems, machine learning, and other artificial intelligence technologies have a crucial role to play in containment and diagnosis in the COVID-19 outbreak. This study developed Enhanced Gravitational Search Optimization with a Hybrid Deep Learning Model (EGSO-HDLM) for COVID-19 diagnoses using epidemiology data. The major aim of designing the EGSO-HDLM model was the identification and classification of COVID-19 using epidemiology data. In order to examine the epidemiology data, the EGSO-HDLM model employed a hybrid convolutional neural network with a gated recurrent unit based fusion (HCNN-GRUF) model. In addition, the hyperparameter optimization of the HCNN-GRUF model was improved by the use of the EGSO algorithm, which was derived by including the concepts of cat map and the traditional GSO algorithm. The design of the EGSO algorithm helps in reducing the ergodic problem, avoiding premature convergence, and enhancing algorithm efficiency. To demonstrate the better performance of the EGSO-HDLM model, experimental validation on a benchmark dataset was performed. The simulation results ensured the enhanced performance of the EGSO-HDLM model over recent approaches.

Area Deprivation and COVID-19 Incidence and Mortality in Bavaria, Germany: A Bayesian Geographical Analysis

Background

Area deprivation has been shown to be associated with various adverse health outcomes including communicable as well as non-communicable diseases. Our objective was to assess potential associations between area deprivation and COVID-19 standardized incidence and mortality ratios in Bavaria over a period of nearly 2 years. Bavaria is the federal state with the highest infection dynamics in Germany and demographically comparable to several other European countries.

Methods

In this retrospective, observational ecological study, we estimated the strength of associations between area deprivation and standardized COVID-19 incidence and mortality ratios (SIR and SMR) in Bavaria, Germany. We used official SARS-CoV-2 reporting data aggregated in monthly periods between March 1, 2020 and December 31, 2021. Area deprivation was assessed using the quintiles of the 2015 version of the Bavarian Index of Multiple Deprivation (BIMD 2015) at district level, analyzing the overall index as well as its single domains.

Results

Deprived districts showed higher SIR and SMR than less deprived districts. Aggregated over the whole period, the SIR increased by 1.04 (95% confidence interval (95% CI): 1.01 to 1.07, p = 0.002), and the SMR by 1.11 (95% CI: 1.07 to 1.16, p < 0.001) per BIMD quintile. This represents a maximum difference of 41% between districts in the most and least deprived quintiles in the SIR and 110% in the SMR. Looking at individual months revealed clear linear association between the BIMD quintiles and the SIR and SMR in the first, second and last quarter of 2021. In the summers of 2020 and 2021, infection activity was low.

Conclusions

In more deprived areas in Bavaria, Germany, higher incidence and mortality ratios were observed during the COVID-19 pandemic with particularly strong associations during infection waves 3 and 4 in 2020/2021. Only high infection levels reveal the effect of risk factors and socioeconomic inequalities. There may be confounding between the highly deprived areas and border regions in the north and east of Bavaria, making the relationship between area deprivation and infection burden more complex. Vaccination appeared to balance incidence and mortality rates between the most and least deprived districts. Vaccination makes an important contribution to health equality.

On the Parametrization of Epidemiologic Models—Lessons from Modelling COVID-19 Epidemic

Numerous prediction models of SARS-CoV-2 pandemic were proposed in the past. Unknown parameters of these models are often estimated based on observational data. However, lag in case-reporting, changing testing policy or incompleteness of data lead to biased estimates. Moreover, parametrization is time-dependent due to changing age-structures, emerging virus variants, non-pharmaceutical interventions, and vaccination programs. To cover these aspects, we propose a principled approach to parametrize a SIR-type epidemiologic model by embedding it as a hidden layer into an input-output non-linear dynamical system (IO-NLDS). Observable data are coupled to hidden states of the model by appropriate data models considering possible biases of the data. This includes data issues such as known delays or biases in reporting. We estimate model parameters including their time-dependence by a Bayesian knowledge synthesis process considering parameter ranges derived from external studies as prior information. We applied this approach on a specific SIR-type model and data of Germany and Saxony demonstrating good prediction performances. Our approach can estimate and compare the relative effectiveness of non-pharmaceutical interventions and provide scenarios of the future course of the epidemic under specified conditions. It can be translated to other data sets, i.e., other countries and other SIR-type models.

Advanced modelling of commuter choice model and work from home during COVID-19 restrictions in Australia

The decision to work from home (WFH) or to commute during COVID-19 is having a major structural impact on individuals' travel, work and lifestyle. There are many possible factors influencing this non-marginal change, some of which are captured by objective variables while others are best represented by a number of underlying latent traits captured by attitudes towards WFH and the use of specific modes of transport for the commute that have a bio-security risk such as public transport (PT). We develop and implement a hybrid choice model to investigate the sources of influence, accounting for the endogenous nature of latent soft variables for workers in metropolitan areas in New South Wales and Queensland. The data was collected between September-October 2020, during a period of no lockdown and relatively minor restrictions on workplaces and public gatherings. The results show that one of the most important attributes defining the WFH loving attitude is the workplace policy towards WFH, with workers that can decide where to work having a higher probability of WFH, followed by those that are being directed to, relative to other workplace policies. The bio-security concern with using shared modes such as public transport is a key driver of WFH and choosing to commute via the safer environment of the private car.

Modeling recapitulates the heterogeneous outcomes of SARS-CoV-2 infection and quantifies the differences in the innate immune and CD8 T-cell responses between patients experiencing mild and severe symptoms

SARS-CoV-2 infection results in highly heterogeneous outcomes, from cure without symptoms to acute respiratory distress and death. Empirical evidence points to the prominent roles of innate immune and CD8 T-cell responses in determining the outcomes. However, how these immune arms act in concert to elicit the outcomes remains unclear. Here, we developed a mathematical model of within-host SARS-CoV-2 infection that incorporates the essential features of the innate immune and CD8 T-cell responses. Remarkably, by varying the strengths and timings of the two immune arms, the model recapitulated the entire spectrum of outcomes realized. Furthermore, model predictions offered plausible explanations of several confounding clinical observations, including the occurrence of multiple peaks in viral load, viral recrudescence after symptom loss, and prolonged viral positivity. We applied the model to analyze published datasets of longitudinal viral load measurements from patients exhibiting diverse outcomes. The model provided excellent fits to the data. The best-fit parameter estimates indicated a nearly 80-fold stronger innate immune response and an over 200-fold more sensitive CD8 T-cell response in patients with mild compared to severe infection. These estimates provide quantitative insights into the likely origins of the dramatic inter-patient variability in the outcomes of SARS-CoV-2 infection. The insights have implications for interventions aimed at preventing severe disease and for understanding the differences between viral variants.