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BackgroundWastewater surveillance has expanded globally to monitor the spread of infectious diseases. An inherent challenge is substantial noise and bias in wastewater data due to their sampling and quantification process, leading to the limited applicability of wastewater surveillance as a monitoring tool and the difficulty.AimIn this study, we present an analytical framework for capturing the growth trend of circulating infections from wastewater data and conducting scenario analyses to guide policy decisions.MethodsWe developed a mathematical model for translating the observed SARS-CoV-2 viral load in wastewater into effective reproduction numbers. We used an extended Kalman filter to infer underlying transmissions by smoothing out observational noise. We also illustrated the impact of different countermeasures such as expanded vaccinations and non-pharmaceutical interventions on the projected number of cases using three study areas in Japan as an example.ResultsOur analyses showed an adequate fit to the data, regardless of study area and virus quantification method, and the estimated reproduction numbers derived from wastewater data were consistent with notification-based reproduction numbers. Our projections showed that a 10-20% increase in vaccination coverage or a 10% reduction in contact rate may suffice to initiate a declining trend in study areas.ConclusionOur study demonstrates how wastewater data can be used to track reproduction numbers and perform scenario modelling to inform policy decisions. The proposed framework complements conventional clinical surveillance, especially when reliable and timely epidemiological data are not available.

In late January 2023, mpox cases without a travel history started to be frequently reported in Japan. As of 14 March 2023, the total number of cases reached 45 with an apparent sign of sustained local transmission. Compared with many of the previously affected countries, Japan is more closely connected with other Asian countries. In the current global mpox outbreak, Asia has been the least affected region so far with limited or no vaccine rollout. As a result, many countries in this region (including low- and middle-income countries) are left with a large susceptible population to mpox. If local transmission is established in these countries, the global spread of mpox may reemerge.

BackgroundThe mpox outbreak in the Netherlands started winding down before the mpox vaccination programme was initiated. Most cases were men who have sex with men (MSM). We investigated whether the decline in mpox was attributed to depletion of susceptible MSM or behavioural changes.MethodsWe developed a transmission model that was fitted to data on mpox cases in the Netherlands until 25 July 2022, when the mpox vaccination programme started. We included behavioural changes, namely less casual partners and shorter time until mpox cases abstain from sexual contacts.FindingsWithout behavioural changes, the peak in modelled mpox cases matched observations, but the decline was less steep than observed. With behavioural changes in July 2022, we estimated a 13-24% decline in casual partners and halving of the infectious time until sexual abstinence. When vaccination started, 64% of MSM with very high sexual activity in the model had been infected. Counterfactual model scenarios revealed that the outbreak could have waned by October 2022 even without the vaccination programme. Import of mpox cases at the end of 2022 could not result in major outbreaks.InterpretationThe limited size of the mpox outbreak in the Netherlands can be ascribed to depletion of susceptible MSM with high levels of sexual activity. The subsequent decline was accelerated by behavioural changes in July 2022. Immunity due to infection and vaccination among those most sexually active diminishes the risk of resurgence of mpox.FundingFM received funding from Japan Society for the Promotion of Science (Number 20J00793).

Many countries affected by the global outbreak of monkeypox in 2022 have observed a decline in cases. Our mathematical model incorporating empirical estimates of the heavy-tailed sexual partnership distribution among men who have sex with men (MSM) suggests that monkeypox epidemics can hit the infection-derived herd immunity threshold and begin to decline with less than 1% of sexually active MSM population infected regardless of interventions or behavioural changes. Consistently, we found that many countries and US states experienced an epidemic peak with cumulative cases of around 0.1–0.7% of MSM population. The observed decline in cases may not necessarily be attributable to interventions or behavioural changes primarily, although continuing these approaches in the most effective manner is still warranted to minimise total epidemic size.

Background Since the roll-out of COVID-19 vaccines in late 2020 and throughout 2021, European governments have relied on mathematical modelling to inform policy decisions about COVID-19 vaccination. Aim We present a scenario-based modelling analysis in the Netherlands during summer 2021, to inform whether to extend vaccination to adolescents (12–17-year-olds) and children (5–11-year-olds). Methods We developed a deterministic, age-structured susceptible-exposed-infectious-recovered (SEIR) model and compared modelled incidences of infections, hospital and intensive care admissions, and deaths per 100,000 people across vaccination scenarios, before the emergence of the Omicron variant. Results Our model projections showed that, on average, upon the release of all non-pharmaceutical control measures on 1 November 2021, a large COVID-19 wave may occur in winter 2021/22, followed by a smaller, second wave in spring 2022, regardless of the vaccination scenario. The model projected reductions in infections/severe disease outcomes when vaccination was extended to adolescents and further reductions when vaccination was extended to all people over 5 years-old. When examining projected disease outcomes by age group, individuals benefitting most from extending vaccination were adolescents and children themselves. We also observed reductions in disease outcomes in older age groups, particularly of parent age (30–49 years), when children and adolescents were vaccinated, suggesting some prevention of onward transmission from younger to older age groups. Conclusions While our scenarios could not anticipate the emergence/consequences of SARS-CoV-2 Omicron variant, we illustrate how our approach can assist decision making. This could be useful when considering to provide booster doses or intervening against future infection waves.

The disinfection susceptibilities of viruses vary even among variants, yet the inactivation efficiency of a certain virus genotype, species, or genus was determined based on the susceptibility of its laboratory strain. The objectives were to evaluate the variability in susceptibilities to free chlorine, UV254, and ozone among 13 variants of coxsackievirus B5 (CVB5) and develop the model allowing for predicting the overall inactivation of heterogeneous CVB5. Our results showed that the susceptibilities differed by up to 3.4-fold, 1.3-fold, and 1.8-fold in free chlorine, UV254, and ozone, respectively. CVB5 in genogroup B exhibited significantly lower susceptibility to free chlorine and ozone than genogroup A, where the laboratory strain, Faulkner, belongs. The capsid protein in genogroup B contained a lower number of sulfur-containing amino acids, readily reactive to oxidants. We reformulated the Chick-Watson model by incorporating the probability distributions of inactivation rate constants to capture the heterogeneity. This expanded Chick-Watson model indicated that up to 4.2-fold larger free chlorine CT is required to achieve 6-log inactivation of CVB5 than the prediction by the Faulkner strain. Therefore, it is recommended to incorporate the variation in disinfection susceptibilities for predicting the overall inactivation of a certain type of viruses.

Inactivation kinetics of enterovirus by disinfection is often studied using a single laboratory strain of a given genotype. Environmental variants of enterovirus are genetically distinct from the corresponding laboratory strain, yet it is poorly understood how these genetic differences affect inactivation. Here we evaluated the inactivation kinetics of nine coxsackievirus B3 (CVB3), ten coxsackievirus B4 (CVB4), and two echovirus 11 (E11) variants by free chlorine and ultraviolet irradiation (UV). The inactivation kinetics by free chlorine were genotype- (i.e., susceptibility: CVB5CVB3 ≈ CVB4E11) and genogroup-dependent and exhibited up to 15-fold difference among the tested viruses. In contrast, only minor (up to 1.3-fold) differences were observed in the UV inactivation kinetics. The differences in variability between the two disinfectants could be rationalized by their respective inactivation mechanisms: inactivation by UV mainly depends on the genomic size and composition, which was similar for all viruses tested, whereas free chlorine targets the viral capsid protein, which exhibited critical differences between genogroups and genotypes. Finally, we integrated the observed variability in inactivation rate constants into an expanded Chick-Watson model to estimate the overall inactivation of an enterovirus consortium. The results highlight that the distribution of inactivation rate constants and the abundance of each genotype are essential parameters to accurately predict the overall inactivation of an enterovirus population by free chlorine. We conclude that predictions based on inactivation data of a single variant or reference pathogen alone likely overestimate the true disinfection efficiency of free chlorine.

In May 2022, monkeypox outbreaks have been reported in countries not endemic for monkeypox. We estimated the monkeypox incubation period, using reported exposure and symptom-onset times for 18 cases detected and confirmed in the Netherlands up to 31 May 2022. Mean incubation period was 9.0 days* (5th–95th percentiles: 4.2–17.3), underpinning the current recommendation to monitor or isolate/quarantine case contacts for 21 days. However, as the incubation period may differ between different transmission routes, further epidemiological investigations are needed.

In May 2022 outbreaks of monkeypox have been reported in countries where the monkeypox virus is not endemic. We estimate the incubation period for monkeypox, using the reported time of exposure and symptom onset for 18 confirmed cases detected in the Netherlands up to 31st May 2022. The mean incubation period was 8.5 days, ranging from 4.2 to 17.3 days (5th to 95th percentiles). These findings underpin 21 days for monitoring or quarantining of case contacts.

SUMMARYBackgroundSurveillance of SARS-CoV-2 in wastewater offers an unbiased and near real-time tool to track circulation of SARS-CoV-2 at a local scale, next to other epidemic indicators such as hospital admissions and test data. However, individual measurements of SARS-CoV-2 in sewage are noisy, inherently variable, and can be left-censored.AimWe aimed to infer latent virus loads in a comprehensive sewage surveillance program that includes all sewage treatment plants (STPs) in the Netherlands and covers 99.6% of the Dutch population.MethodsA multilevel Bayesian penalized spline model was developed and applied to estimate time- and STP-specific virus loads based on water flow adjusted SARS-CoV-2 qRT-PCR data from 1-4 sewage samples per week for each of the >300 STPs.ResultsThe model provided an adequate fit to the data and captured the epidemic upsurges and downturns in the Netherlands, despite substantial day-to-day measurement variation. Estimated STP virus loads varied by more than two orders of magnitude, from approximately 1012 (virus particles per 100,000 persons per day) in the epidemic trough in August 2020 to almost 1015 in many STPs in January 2022. Epidemics at the local levels were slightly shifted between STPs and municipalities, which resulted in less pronounced peaks and troughs at the national level.ConclusionAlthough substantial day-to-day variation is observed in virus load measurements, wastewater-based surveillance of SARS-CoV-2 can track long-term epidemic progression at a local scale in near real-time, especially at high sampling frequency.

IntroductionDespite the high COVID-19 vaccination coverage among adults, there is concern over a peak in SARS-CoV-2 infections in the coming months. To help ensure that healthcare systems are not overwhelmed in the event of a new wave of SARS-CoV-2 infections, many countries have extended vaccination to adolescents (those aged 12-17 years) and may consider further extending to children aged 5-11 years. However, there is considerable debate about whether or not to vaccinate healthy adolescents and children against SARS-CoV-2 because, while vaccination of children and adolescents may limit transmission from these groups to other, more vulnerable groups, adolescents and children themselves have limited risk of severe disease if infected and may experience adverse events from vaccination. To quantify the benefits of extending COVID-19 vaccination beyond adults we compare daily cases, hospital admissions, and intensive care (IC) admissions for vaccination in adults only, those 12 years and above, and those 5 years and above.Methods and FindingsWe developed a deterministic, age-structured susceptible-exposed-infectious-recovered (SEIR) model to simulate disease outcomes (e.g., cases, hospital admissions, IC admissions) under different vaccination scenarios. The model is partitioned into 10-year age bands (0-9, 10-19, …, 70-79, 80+) and accounts for differences in susceptibility and infectiousness by age group, seasonality in transmission rate, modes of vaccine protection (e.g., infection, transmission), and vaccine characteristics (e.g., vaccine effectiveness). Model parameters are estimated by fitting the model piecewise to daily cases from the Dutch notification database Osiris from 01 January 2020 to 22 June 2021. Forward simulations are performed from 22 June 2021 to 31 March 2022. We performed sensitivity analyses in which vaccine-induced immunity waned.We found that upon relaxation of all non-pharmaceutical control measures a large wave occurred regardless of vaccination strategy. We found overall reductions of 5.7% (4.4%, 6.9%) of cases, 2.0% (0.7%, 3.2%) of hospital admissions, and 1.7% (0.6%, 2.8%) of IC admissions when those 12 years and above were vaccinated compared to vaccinating only adults. When those 5 years and above were vaccinated we observed reductions of 8.7% (7.5%, 9.9%) of cases, 3.2% (2.0%, 4.5%) of hospital admissions, and 2.4% (1.2%, 3.5%) of IC admissions compared to vaccination in adults only. Benefits of extending vaccination were larger within the age groups included in the vaccination program extension than in other age groups. The benefits of vaccinating adolescents and children were smaller if vaccine protection against infection, hospitalization, and transmission (once infected) wanes.DiscussionOur results highlight the benefits of extending COVID-19 vaccination programs beyond adults to reduce infections and severe outcomes in adolescents and children and in the wider population. A reduction of infections in school-aged children/adolescents may have the added benefit of reducing the need for school closures during a new wave. Additional control measures may be required in future to prevent a large wave despite vaccination program extensions. While the results presented here are based on population characteristics and the COVID-19 vaccination program in The Netherlands, they may provide valuable insights for other countries who are considering COVID-19 vaccination program extensions.

BackgroundThe proportion of SARS-CoV-2 positive persons who are asymptomatic – and whether this proportion is age-dependent – are still open research questions. Because an unknown proportion of reported symptoms among SARS-CoV-2 positives will be attributable to another infection or affliction, the observed, or ‘crude’ proportion without symptoms may underestimate the proportion of persons without symptoms that are caused by SARS-CoV-2 infection.MethodsBased on a large population-based serological study comprising test results on seropositivity and self-reported symptom history conducted in April/May 2020 in the Netherlands (n=3147), we estimated the proportion of reported symptoms among those persons infected with SARS-CoV-2 that is attributable to this infection, where the set of relevant symptoms fulfills the ECDC case definition of COVID-19, using inferential methods for the attributable risk (AR). Generalised additive regression modelling was used to estimate the age-dependent relative risk (RR) of reported symptoms, and the AR and asymptomatic proportion (AP) were calculated from the fitted RR.ResultsUsing age-aggregated data, the estimated AP was 70% (95% CI: 65-77%). The estimated AP decreased with age, from 80% (95% CI: 67-100%) for the ConclusionWhereas the ‘crude’ AP represents a lower bound for the proportion of persons infected with SARS-CoV-2 without COVID-19 symptoms, the AP as estimated via an attributable risk approach represents an upper bound. Age-specific AP estimates can inform the implementation of public health actions such as targetted virological testing and therefore enhance containment strategies.

The 2020 Olympic/Paralympic Games have been postponed to 2021, due to the COVID-19 pandemic. We developed a model that integrated source–environment–receptor pathways to evaluate how preventive efforts can reduce the infection risk among spectators at the opening ceremony of Tokyo Olympic Games. We simulated viral loads of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emitted from infectors through talking/coughing/sneezing and modeled temporal environmental behaviors, including virus inactivation and transfer. We performed Monte Carlo simulations to estimate the expected number of newly infected individuals with and without preventive measures, yielding the crude probability of a spectator being an infector among the 60,000 people expected to attend the opening ceremony. Two indicators, i.e., the expected number of newly infected individuals and the newly infected individuals per infector entry, were proposed to demonstrate the extent of achievable infection risk reduction levels by implementing possible preventive measures. A no-prevention scenario produced 1.5–1.7 newly infected individuals per infector entry, whereas a combination of cooperative preventive measures by organizers and the spectators achieved a 99% risk reduction, corresponding to 0.009–0.012 newly infected individuals per infector entry. The expected number of newly infected individuals was calculated as 0.005 for the combination of cooperative preventive scenarios with the crude probability of a spectator being an infector of 1 × 10−5. Based on our estimates, a combination of cooperative preventions between organizers and spectators is required to prevent a viral spread at the Tokyo Olympic/Paralympic Games. Further, under the assumption that society accepts < 10 newly infected persons traced to events held during the entire Olympic/Paralympic Games, we propose a crude probability of infectors of < 5 × 10−5 as a benchmark for the suppression of the infection. This is the first study to develop a model that can assess the infection risk among spectators due to exposure pathways at a mass gathering event., Graphical abstract Image, graphical abstract

The disinfection susceptibilities of viruses vary even among variants, yet the inactivation efficiency of a certain virus genotype, species, or genus was determined based on the susceptibility of its laboratory strain. The objectives were to evaluate the variability in susceptibilities to free chlorine, UV

Wastewater-based epidemiology (WBE) is one of the most promising approaches to effectively monitor the spread of COVID-19. The virus concentration in faeces and its temporal variations are essential information for WBE. While some clinical studies have reported SARS-CoV-2 concentrations in faeces, the value varies amongst patients and changes over time. The present study aimed to examine how the temporal variations in the concentration of virus in faeces affect the monitoring of disease incidence. We reanalysed the experimental findings of clinical studies to estimate the duration of virus shedding and the faecal virus concentration. Available experimental data as of 23 October 2020 were collected. The viral shedding kinetics was modelled, and the dynamic model was fitted to the collected data by a Bayesian framework. Using posterior distributions, the duration of viral shedding and the concentration of virus copies in faeces over time were computed. We estimated the median concentration of SARS-CoV-2 in faeces as 3.4 (95% CrI: 0.24–6.5) log copies per gram-faeces over the shedding period, and our model implied that the duration of viral shedding was 26.0 days (95% CrI: 21.7–34.9), given the current standard quantification limit (Ct = 40). With simulated incidences, our results also indicated that a one-week delay between symptom onset and wastewater sampling increased the estimation of incidence by a factor of 17.2 (i.e., 101.24 times higher). Our results demonstrated that the temporal variation in virus concentration in faeces affects microbial monitoring systems such as WBE. The present study also implied the need for adjusting the estimates of virus concentration in faeces by incorporating the kinetics of unobserved concentrations. The method used in this study is easily implemented in further simulations; therefore, the results of this study might contribute to enhancing disease surveillance and risk assessments that require quantities of virus to be excreted into the environment., Graphical abstract Unlabelled Image

Background: Foodborne norovirus outbreak data in Japan from 2005–2006, involving virological surveillance of all symptomatic and asymptomatic individuals, were reanalyzed to estimate the asymptomatic ratio of norovirus infection along with the risk of infection and the probability of virus shedding. Methods: Employing a statistical model that is considered to capture the data-generating process of the outbreak and virus surveillance, maximum likelihood estimation of the asymptomatic ratio was implemented. Results: Assuming that all norovirus outbreaks (n = 55) were the result of random sampling from an identical distribution and ignoring genogroup and genotype specificities, the asymptomatic ratio was estimated at 32.1% (95% confidence interval [CI], 27.7–36.7). Although not significant, separate estimation of the asymptomatic ratio of the GII.4 genotype appeared to be greater than other genotypes and was estimated at 40.7% (95% CI, 32.8–49.0). Conclusion: The present study offered the first explicit empirical estimates of the asymptomatic ratio of norovirus infection in natural infection settings. The estimate of about 30% was consistent with those derived from volunteer challenge studies. Practical difficulty in controlling GII.4 outbreaks was supported by the data, considering that a large estimate of the asymptomatic ratio was obtained for the GII.4 genotype.

For the control of COVID-19, vaccination programmes provide a long-term solution. The amount of available vaccines is often limited, and thus it is crucial to determine the allocation strategy. While mathematical modelling approaches have been used to find an optimal distribution of vaccines, there is an excessively large number of possible allocation schemes to be simulated. Here, we propose an algorithm to find a near-optimal allocation scheme given an intervention objective such as minimization of new infections, hospitalizations, or deaths, where multiple vaccines are available. The proposed principle for allocating vaccines is to target subgroups with the largest reduction in the outcome of interest. We use an approximation method to reconstruct the age-specific transmission intensity (the next generation matrix), and express the expected impact of vaccinating each subgroup in terms of the observed incidence of infection and force of infection. The proposed approach is firstly evaluated with a simulated epidemic and then applied to the epidemiological data on COVID-19 in the Netherlands. Our results reveal how the optimal allocation depends on the objective of infection control. In the case of COVID-19, if we wish to minimize deaths, the optimal allocation strategy is not efficient for minimizing other outcomes, such as infections. In simulated epidemics, an allocation strategy optimized for an outcome outperforms other strategies such as the allocation from young to old, from old to young, and at random. Our simulations clarify that the current policy in the Netherlands (i.e., allocation from old to young) was concordant with the allocation scheme that minimizes deaths. The proposed method provides an optimal allocation scheme, given routine surveillance data that reflect ongoing transmissions. This approach to allocation is useful for providing plausible simulation scenarios for complex models, which give a more robust basis to determine intervention strategies., Author summary Vaccination is the key to controlling the ongoing COVID-19 pandemic. In the early stages of an epidemic, there is shortage of vaccines. Here, we propose an algorithm that computes an optimal vaccine distribution among groups for different intervention objective (e.g., minimizing new infections, hospitalizations, or deaths). This method is applicable even when multiple vaccines are available. Our results reveal that an allocation scheme optimized for one specific objective is not necessarily efficient for another, indicating the importance of determining the precise objective in the decision making process at the early phase of distributions. Often, data are scarce in the midst of an epidemics. The proposed method requires routine surveillance data on the number of cases to determine the best possible allocation of vaccines.

The actual number of individuals infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is difficult to estimate using a case-reporting system (i.e., passive surveillance) alone because of asymptomatic infection. While wastewater-based epidemiology has been implemented as an alternative/additional monitoring tool to reduce reporting bias, the relationship between passive and wastewater surveillance data has not yet been explicitly examined. As there is strong age dependency in the symptomatic ratio of SARS-CoV-2 infections, here, we aimed to estimate i) an age-dependent association between the number of reported cases and viral load in wastewater and ii) the time lag between these time series. The viral load in wastewater was modeled as a combination of contributions from virus shedding by different age groups, incorporating the delay, and fitted with daily case count data collected from the Massachusetts Department of Public Health and SARS-CoV-2 RNA concentration in wastewater recorded by the Massachusetts Water Resources Authority. The estimated lag between the time series of viral loads in wastewater and of reported cases was 10.8 (95% confidence interval: 10.2–11.6) and 8.8 (8.4–9.1) days for the northern and southern areas of the wastewater treatment plant, respectively. The estimated contribution rate of a reported case to the viral load in wastewater in the 0–19 yr age group was 0.38 (0.35–0.41) and 0.40 (0.37–0.43) for the northern and southern areas, and that in the 80+ yr age group was 0.67 (0.65–0.69) and 0.51 (0.49–0.52) for the northern and southern areas, respectively. The estimated lag between these time series suggested the predictability of reported cases 10 days later using viral loads in wastewater. The contribution of a reported case in passive surveillance to the viral load in wastewater differed by age, suggesting a large variation in viral shedding kinetics among age groups., Graphical abstract Unlabelled Image

Transmission potential and severity of pneumonic plague in Madagascar were assessed. Accounting for reporting delay, the reproduction number was estimated at 1.73. The case fatality risk was estimated as 5.5%. Expected numbers of exported cases from Madagascar were estimated across the world and all estimates were below 1 person from August to October, 2017.

Background The proportion of SARS-CoV-2 positive persons who are asymptomatic—and whether this proportion is age-dependent—are still open research questions. Because an unknown proportion of reported symptoms among SARS-CoV-2 positives will be attributable to another infection or affliction, the observed, or 'crude' proportion without symptoms may underestimate the proportion of persons without symptoms that are caused by SARS-CoV-2 infection. Methods Based on two rounds of a large population-based serological study comprising test results on seropositivity and self-reported symptom history conducted in April/May and June/July 2020 in the Netherlands (n = 7517), we estimated the proportion of reported symptoms among those persons infected with SARS-CoV-2 that is attributable to this infection, where the set of relevant symptoms fulfills the ECDC case definition of COVID-19, using inferential methods for the attributable risk (AR). Generalised additive regression modelling was used to estimate the age-dependent relative risk (RR) of reported symptoms, and the AR and asymptomatic proportion (AP) were calculated from the fitted RR. Results Using age-aggregated data, the 'crude' AP was 37% but the model-estimated AP was 65% (95% CI 63–68%). The estimated AP varied with age, from 74% (95% CI 65–90%) for Conclusion Whereas the 'crude' AP represents a lower bound for the proportion of persons infected with SARS-CoV-2 without COVID-19 symptoms, the AP as estimated via an attributable risk approach represents an upper bound. Age-specific AP estimates can inform the implementation of public health actions such as targetted virological testing and therefore enhance containment strategies.

We propose a mathematical framework to analyze and interpret the outcomes of human challenge trials. We present plausible infection risks with HCoV-229E and SARS-CoV-2 over a wide range of infectious dose, and suggest ways to improve the design of future trials and to translate its outcomes to the general population.One sentence summaryWe rephrase dose-response models in terms of heterogeneity in susceptibility in order to present the possible range of infection risks for endemic coronaviruses and SARS-CoV-2