The impact of Zika emergence in remote communities in northwestern Ecuador.

The Zika virus (ZIKV) epidemic in Latin America (2015-2016) has primarily been studied in urban centers, with less understanding of its impact on smaller rural communities. To address this gap, we analyzed ZIKV sero-epidemiology in six rural Ecuadorian communities (2018-2019) with varying access to a commercial hub. Seroprevalence ranged from 19% to 54% measured by NS1 blockade of binding ELISA. We observed a decline in ZIKV seroprevalence between 2018 and 2019 that was greater among younger populations, suggesting that the attack rates in the 2015-16 epidemic were significantly higher than our 2018 observations. These data indicate that the 2015-16 epidemic included significant transmission in rural and more remote settings. Our observations of high seroprevalence in our area of study highlights the importance of surveillance and research in rural areas lacking robust health systems to manage future Zika outbreaks and vaccine initiatives.

Reduced effectiveness of repeat influenza vaccination: distinguishing among within-season waning, recent clinical infection, and subclinical infection.

Studies have reported that prior-season influenza vaccination is associated with higher risk of clinical influenza infection among vaccinees. This effect might arise from incomplete consideration of within-season waning and recent infection. Using data from the US Flu Vaccine Effectiveness (VE) Network (2011-2012 to 2018-2019 seasons), we found that repeat vaccinees were vaccinated earlier in a season by one week. After accounting for waning VE, repeat vaccinees were still more likely to test positive for A(H3N2) (OR=1.11, 95%CI:1.02-1.21) but not for influenza B or A(H1N1). We found that clinical infection influenced individuals' decision to vaccinate in the following season while protecting against clinical infection of the same (sub)type. However, adjusting for recent clinical infections did not strongly influence the estimated effect of prior-season vaccination. In contrast, we found that adjusting for subclinical infection could theoretically attenuate this effect. Additional investigation is needed to determine the impact of subclinical infections on VE.

SIRS epidemics with individual heterogeneity of immunity waning.

In the current paper we analyse an extended SIRS epidemic model in which immunity at the individual level wanes gradually at exponential rate, but where the waning rate may differ between individuals, for instance as an effect of differences in immune systems. The model also includes vaccination schemes aimed to reach and maintain herd immunity. We consider both the informed situation where the individual waning parameters are known, thus allowing selection of vaccinees being based on both time since last vaccination as well as on the individual waning rate, and the more likely uninformed situation where individual waning parameters are unobserved, thus only allowing vaccination schemes to depend on time since last vaccination. The optimal vaccination policies for both the informed and uniformed heterogeneous situation are derived and compared with the homogeneous waning model (meaning all individuals have the same immunity waning rate), as well as to the classic SIRS model where immunity at the individual level drops from complete immunity to complete susceptibility in one leap. It is shown that the classic SIRS model requires least vaccines, followed by the SIRS with homogeneous gradual waning, followed by the informed situation for the model with heterogeneous gradual waning. The situation requiring most vaccines for herd immunity is the most likely scenario, that immunity wanes gradually with unobserved individual heterogeneity. For parameter values chosen to mimic COVID-19 and assuming perfect initial immunity and cumulative immunity of 12 months, the classic homogeneous SIRS epidemic suggests that vaccinating individuals every 15 months is sufficient to reach and maintain herd immunity, whereas the uninformed case for exponential waning with rate heterogeneity corresponding to a coefficient of variation being 0.5, requires that individuals instead need to be vaccinated every 4.4 months.

Treatment Effect Waning Assumptions: A Review of National Institute of Health and Care Excellence Technology Appraisals.

OBJECTIVES: This study aims to review the National Institute of Health and Care Excellence (NICE) technology assessments to gain insights into the implementation of treatment effect (TE) waning, whereby the hazard or survival in an assessed technology converges to that of the comparator. This analysis aims to contribute to inform future guidance in this area. METHODS: Technology appraisals published October 20, 2021 to September 20, 2023 were reviewed and data extracted on TE waning circumstances, methods, and rationale to compile a database based on 3 research questions: When are TE waning assumptions used? What methods are used? Why have the company/Evidence Assessment Group/committee preferred these methods? RESULTS: Both the evidence assessment group/company and the committee included TE waning assumptions in 28 appraisals. There was no pattern of waning assumptions between shorter (<20 years) and longer (>20 years) time horizons. The most prominent time point for applying waning assumptions was at 5 years, with 30 out of 59 (50.8%) of the methods applied used 5 years. Stopping rules were used in 21 out of 30 (70.1%) of the appraisals for which the committee included waning, and waning assumptions were used more in oncology. The most common reason given for including TE waning assumptions was precedent from prior appraisals. CONCLUSIONS: Considerable heterogeneity existed in both the methods used and justifications given for TE waning assumptions. This variability poses a risk of inconsistent decision making. Reliance on past appraisals emphasizes the necessity to advocate for evidence-driven approaches and underscores the demand for guidance on suitable methods for incorporating assumptions.

Perils of Randomized Controlled Trial Survival Extrapolation Assuming Treatment Effect Waning: Why the Distinction Between Marginal and Conditional Estimates Matters.

OBJECTIVES: A long-term, constant, protective treatment effect is a strong assumption when extrapolating survival beyond clinical trial follow-up; hence, sensitivity to treatment effect waning is commonly assessed for economic evaluations. Forcing a hazard ratio (HR) to 1 does not necessarily estimate loss of individual-level treatment effect accurately because of HR selection bias. A simulation study was designed to explore the behavior of marginal HRs under a waning conditional (individual-level) treatment effect and demonstrate bias in forcing a marginal HR to 1 when the estimand is "survival difference with individual-level waning". METHODS: Data were simulated under 4 parameter combinations (varying prognostic strength of heterogeneity and treatment effect). Time-varying marginal HRs were estimated in scenarios where the true conditional HR attenuated to 1. Restricted mean survival time differences, estimated having constrained the marginal HR to 1, were compared with true values to assess bias induced by marginal constraints. RESULTS: Under loss of conditional treatment effect, the marginal HR took a value >1 because of covariate imbalances. Constraining this value to 1 lead to restricted mean survival time difference bias of up to 0.8 years (57% increase). Inflation of effect size estimates also increased with the magnitude of initial protective treatment effect. CONCLUSIONS: Important differences exist between survival extrapolations assuming marginal versus conditional treatment effect waning. When a marginal HR is constrained to 1 to assess efficacy under individual-level treatment effect waning, the survival benefits associated with the new treatment will be overestimated, and incremental cost-effectiveness ratios will be underestimated.

Household transmission of Omicron variant of SARS-CoV-2 under conditions of hybrid immunity-a prospective study in Germany.

PURPOSE: We investigated the protection offered by vaccinations and previous infections for the household transmission of Omicron variant of SARS-CoV-2. METHODS: 34,666 participants of the German DigiHero cohort study with two or more household members were invited to a prospective household transmission study between June and December 2022. In case of a positive SARS-CoV-2 test in a household, symptom diaries were completed for at least 14 days. Dry blood spots (DBS) were taken from all household members at the beginning and six to eight weeks later. DBS were analyzed for SARS-CoV-2 antibodies. RESULTS: 1191 individuals from 457 households participated. The risk of acquiring a SARS-CoV-2 infection decreased with higher S-titer levels at the time of exposure (from 80% at titer of 0 binding antibody units (BAU)/ml to 20% at titer of 3000 BAU/ml) and increased linearly with the time since vaccination/previous infection (20% for less than one month to 80% at one year). Transmission probability was also reduced when the symptoms of the primary case were mild and if preventive measures were implemented. CONCLUSION: Vaccinations/previous infections offer a high protection against infection with the Omicron variant for a few months only, supporting the notion of seasonal circulation of the virus.

Annual risk of hepatitis E virus infection and seroreversion: Insights from a serological cohort in Sitakunda, Bangladesh.

Hepatitis E virus (HEV) is a major cause of acute jaundice in South Asia. Gaps in our understanding of transmission are driven by non-specific symptoms and scarcity of diagnostics, impeding rational control strategies. In this context, serological data can provide important proxy measures of infection. We enrolled a population-representative serological cohort of 2,337 individuals in Sitakunda, Bangladesh. We estimated the annual risks of HEV infection and seroreversion both using serostatus changes between paired serum samples collected 9 months apart, and by fitting catalytic models to the age-stratified cross-sectional seroprevalence. At baseline, 15% (95 CI: 14-17%) of people were seropositive, with seroprevalence highest in the relatively urban south. During the study, 27 individuals seroreverted (annual seroreversion risk: 15%, 95 CI: 10-21%), and 38 seroconverted (annual infection risk: 3%, 95CI: 2-5%). Relying on cross-sectional seroprevalence data alone, and ignoring seroreversion, underestimated the annual infection risk five-fold (0.6%, 95 CrI: 0.5-0.6%). When we accounted for the observed seroreversion in a reversible catalytic model, infection risk was more consistent with measured seroincidence. Our results quantify HEV infection risk in Sitakunda and highlight the importance of accounting for seroreversion when estimating infection incidence from cross-sectional seroprevalence data.

Differences in virus and immune dynamics for SARS-CoV-2 Delta and Omicron infections by age and vaccination histories.

Vaccination against COVID-19 was integral to controlling the pandemic that persisted with the continuous emergence of SARS-CoV-2 variants. Using a mathematical model describing SARS-CoV-2 within-host infection dynamics, we estimate differences in virus and immunity due to factors of infecting variant, age, and vaccination history (vaccination brand, number of doses and time since vaccination). We fit our model in a Bayesian framework to upper respiratory tract viral load measurements obtained from cases of Delta and Omicron infections in Singapore, of whom the majority only had one nasopharyngeal swab measurement. With this dataset, we are able to recreate similar trends in URT virus dynamics observed in past within-host modelling studies fitted to longitudinal patient data.We found that Omicron had higher R0,within values than Delta, indicating greater initial cell-to-cell spread of infection within the host. Moreover, heterogeneities in infection dynamics across patient subgroups could be recreated by fitting immunity-related parameters as vaccination history-specific, with or without age modification. Our model results are consistent with the notion of immunosenescence in SARS-CoV-2 infection in elderly individuals, and the issue of waning immunity with increased time since last vaccination. Lastly, vaccination was not found to subdue virus dynamics in Omicron infections as well as it had for Delta infections.This study provides insight into the influence of vaccine-elicited immunity on SARS-CoV-2 within-host dynamics, and the interplay between age and vaccination history. Furthermore, it demonstrates the need to disentangle host factors and changes in pathogen to discern factors influencing virus dynamics. Finally, this work demonstrates a way forward in the study of within-host virus dynamics, by use of viral load datasets including a large number of patients without repeated measurements.

Measuring waning protection from seasonal influenza vaccination during nine influenza seasons, Ontario, Canada, 2010/11 to 2018/19.

BackgroundWaning immunity from seasonal influenza vaccination can cause suboptimal protection during peak influenza activity. However, vaccine effectiveness studies assessing waning immunity using vaccinated and unvaccinated individuals are subject to biases.AimWe examined the association between time since vaccination and laboratory-confirmed influenza to assess the change in influenza vaccine protection over time.MethodsUsing linked laboratory and health administrative databases in Ontario, Canada, we identified community-dwelling individuals aged ≥ 6 months who received an influenza vaccine before being tested for influenza by RT-PCR during the 2010/11 to 2018/19 influenza seasons. We estimated the adjusted odds ratio (aOR) for laboratory-confirmed influenza by time since vaccination (categorised into intervals) and for every 28 days.ResultsThere were 53,065 individuals who were vaccinated before testing for influenza, with 10,264 (19%) influenza-positive cases. The odds of influenza increased from 1.05 (95% CI: 0.91-1.22) at 42-69 days after vaccination and peaked at 1.27 (95% CI: 1.04-1.55) at 126-153 days when compared with the reference interval (14-41 days). This corresponded to 1.09-times increased odds of influenza every 28 days (aOR = 1.09; 95% CI: 1.04-1.15). Individuals aged 18-64 years showed the greatest decline in protection against influenza A(H1N1) (aORper 28 days = 1.26; 95% CI: 0.97-1.64), whereas for individuals aged ≥ 65 years, it was against influenza A(H3N2) (aORper 28 days = 1.20; 95% CI: 1.08-1.33). We did not observe evidence of waning vaccine protection for individuals aged < 18 years.ConclusionsInfluenza vaccine protection wanes during an influenza season. Understanding the optimal timing of vaccination could ensure robust protection during seasonal influenza activity.

Post-vaccination, post-infection and hybrid immunity against severe cases of COVID-19 and long COVID after infection with SARS-CoV-2 Omicron subvariants, Czechia, December 2021 to August 2023.

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.