This paper explores a model integrating healthcare capacity thresholds and seasonal effects to investigate the synchronization of epidemic cycles with seasonal transmission rates, using parameters reflective of the COVID-19 pandemic. Through bifurcation analysis in the epi-seasonal domain, we identify regions of significant seasonal synchronization related to transmission rate fluctuations, waning immunity, and healthcare capacity thresholds. The model highlights four sources of unpredictability: chaotic regimes, quasiperiodicity, proximity to SNIC or transcritical bifurcations, and bistability. Our findings reveal that chaotic regimes are more predictable than quasiperiodic regimes in epidemiological terms. Synchronizing outbreaks with seasonal cycles, even in chaotic regimes, predominantly results in significant winter outbreaks. Conversely, quasiperiodicity allows outbreaks to occur at any time of the year. Near eradication unpredictability aligns with historical pertussis data, underscoring the model's relevance to real-world epidemics and vaccine schedules. Additionally, we identify a bistability region with potential for abrupt shifts in disease prevalence, triggered by superspreading events or migration.

• Keywords
• Bifurcation, Chaos, Quasiperiodicity, SIRS model, Seasonality,
• MeSH
• COVID-19 * epidemiology   transmission   immunology   MeSH
• Epidemics MeSH
• Epidemiological Models * MeSH
• Humans MeSH
• Pandemics MeSH
• Seasons * MeSH
• SARS-CoV-2 MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH

BACKGROUND: We examined the clinical effectiveness of molnupiravir in reducing deaths in a real-world cohort of adult patients with COVID-19 during the Omicron outbreak. METHODS: This was a population-wide retrospective cohort study in the Czech Republic. We analyzed all 74 541 patients with an officially registered diagnosis of SARS-CoV-2 infection between 1 January and 31 December 2022, aged 18 years or older, treated with molnupiravir. The primary outcome was 30-day all-cause mortality; the secondary outcome was 30-day COVID-19-related mortality. Hazard ratios (HRs) were estimated using stratified Cox regression and the Fine-Gray model. RESULTS: The use of molnupiravir in adult SARS-CoV-2 positive patients was associated with a lower risk of both 30-day all-cause mortality: adjusted HR 0.58 (95% confidence interval, 0.53-0.64; P < .001) and 30-day COVID-19-related mortality: adjusted HR 0.50 (95% confidence interval, 0.42-0.58; P < .001). The effect of molnupiravir was highly significant regardless of sex, Deyo-Charlson Comorbidity Index score, hospitalization status, COVID-19 vaccination status, and patients older than age 65 years. CONCLUSIONS: In this cohort study, early initiation of molnupiravir was associated with a significant reduction in 30-day all-cause and COVID-19-related mortality in adult SARS-CoV-2 positive patients.

• Keywords
• 30-day all-cause mortality, COVID-19, COVID-19-related mortality, SARS-CoV-2 infection, molnupiravir,
• Publication type
• Journal Article MeSH
• Clinical Trial MeSH

BackgroundCOVID-19 remains a major infectious disease with substantial implications for individual and public health including the risk of a post-infection syndrome, long COVID. The continuous changes in dominant variants of SARS-CoV-2 necessitate a careful study of the effect of preventative strategies.AimWe aimed to estimate the effectiveness of post-vaccination, post-infection and hybrid immunity against severe cases requiring oxygen support caused by infections with SARS-CoV-2 variants BA1/2 and BA4/5+, and against long COVID in the infected population and their changes over time.MethodsWe used a Cox regression analysis with time-varying covariates and calendar time and logistic regression applied to national-level data from Czechia from December 2021 until August 2023.ResultsRecently boosted vaccination, post-infection and hybrid immunity provide significant protection against a severe course of COVID-19, while unboosted vaccination more than 10 months ago has a negligible protective effect. The post-vaccination immunity against the BA1/2 or BA4/5+ variants, especially based on the original vaccine types, appears to wane rapidly compared with post-infection and hybrid immunity. Once infected, however, previous immunity plays only a small protective role against long COVID.ConclusionVaccination remains an effective preventative measure against a severe course of COVID-19 but its effectiveness wanes over time thus highlighting the importance of booster doses. Once infected, vaccines may have a small protective effect against the development of long COVID.

• Keywords
• BA1/2, BA4/5, covid-19, hybrid immunity, long covid, vaccine effectiveness, waning,
• MeSH
• COVID-19 * immunology   prevention & control   epidemiology   MeSH
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Post-Acute COVID-19 Syndrome MeSH
• SARS-CoV-2 * immunology   MeSH
• Immunization, Secondary MeSH
• Aged MeSH
• Vaccination MeSH
• COVID-19 Vaccines * immunology   administration & dosage   MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Geographicals
• Czech Republic epidemiology   MeSH
• Names of Substances
• COVID-19 Vaccines * MeSH

We present a novel approach to estimate the time-varying ascertainment rate in almost real-time, based on the surveillance of positively tested infectious and hospital admission data. We also address the age dependence of the estimate. The ascertainment rate estimation is based on the Bayes theorem. It can be easily calculated and used (i) as part of a mechanistic model of the disease spread or (ii) to estimate the unreported infections or changes in their proportion in almost real-time as one of the early-warning signals in case of undetected outbreak emergence. The paper also contains a case study of the COVID-19 epidemic in the Czech Republic. The case study demonstrates the usage of the ascertainment rate estimate in retrospective analysis, epidemic monitoring, explanations of differences between waves, usage in the national Anti-epidemic system, and monitoring of the effectiveness of non-pharmaceutical interventions on Czech nationwide surveillance datasets. The Czech data reveal that the probability of hospitalization due to SARS-CoV-2 infection for the senior population was 12 times higher than for the non-senior population in the monitored period from the beginning of March 2020 to the end of May 2021. In a mechanistic model of COVID-19 spread in the Czech Republic, the ascertainment rate enables us to explain the links between all basic compartments, including new cases, hospitalizations, and deaths.

• MeSH
• Bayes Theorem MeSH
• COVID-19 * epidemiology   MeSH
• Hospitalization MeSH
• Communicable Diseases * MeSH
• Humans MeSH
• Retrospective Studies MeSH
• SARS-CoV-2 MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Geographicals
• Czech Republic epidemiology   MeSH