Initial investigation into the emerging mpox outbreak caused by novel monkeypox virus (MPXV) clade Ib in the eastern Democratic Republic of the Congo has identified signs of sustained human-to-human transmission and epidemiological links to sexual contacts involving female sex workers (FSWs), which have not been observed in previous clade Ia outbreaks. Using mathematical models incorporating age-dependent contact patterns, we quantified the role of frequent sexual interactions as opposed to community contacts in clade Ib's dynamics and found that this additional mode of transmission could explain its increased outbreak potential compared with clade Ia. As with the globally circulating clade IIb, which is transmitted predominantly among men who have sex with men, our findings reinforce the importance of protecting key population groups-specifically FSWs for clade Ib-in controlling ongoing mpox outbreaks.

Artificial intelligence (AI) can offer individualized dietary guidance based on multimodal data collected from various sources, including wearable sensors, high-dimensional multiomics and biomarker analyses, behavioral tracking, and self-reported dietary intake, enabling the emergence of precision nutrition. However, the predictive power and fairness of these models rely on the quality of the data inputs, and measurement errors in any of these underlying data streams can introduce systematic bias, degrade model performance, and disproportionately affect underserved populations. In this review, we examine the central role played by measurement error in AI-driven nutrition tools and evaluate statistical and machine learning approaches for mitigating the impacts of measurement error. We provide structured comparisons exploring both classical methods (e.g., regression calibration, Bayesian models) and emerging AI strategies (e.g., denoising autoencoders, multitask learning, uncertainty-aware deep learning) for correcting biased inputs. We also explore how uncorrected measurement error can perpetuate demographic biases, compromise efforts toward personalized medicine, and exacerbate equity gaps when models are deployed in real-world settings. Our review draws upon evidence across nutrition science, digital health, and algorithmic fairness. We propose a framework and offer actionable strategies for overcoming measurement error that can be implemented by researchers, developers, and regulators working at the intersection of data science and dietary health and seeking to build calibration-aware, inclusive precision nutrition systems.

Infectious disease spread is a multiscale process composed of within-host (biological) and between-host (social) drivers and disentangling them from each other is a central challenge in epidemiology. Here, we introduce VIBES, a multiscale modeling framework that explicitly integrates viral dynamics based on patient-level data with population-level transmission on a data-driven network of social contacts. Using SARS-CoV-2 as a case study, we analyze three emergent epidemic properties, namely the generation time, serial interval, and presymptomatic transmission. First, we established a purely biological baseline, thus independent of the reproduction number (R), from the within-host model, estimating a generation time of 6.3 d for symptomatic individuals and 43.1% presymptomatic transmission. Then, using the full model incorporating social contacts, we found a shorter generation time (5.4 d at R = 3.0) and an increase in presymptomatic transmission (52.8% at R = 3.0), disentangling the impact of social drivers from a purely biological baseline. We further show that as pathogen transmissibility increases (R from 1.3 to 6), competition among infectious individuals shortens the generation time and serial interval by up to 21% and 13%, respectively. Conversely, a social intervention, like isolation, increases the proportion of presymptomatic transmission by about 30%. Our framework also estimates metrics that are challenging to obtain empirically, such as the generation time for asymptomatic individuals (5.6 d; 95%CI: 5.1 to 6.0 at R = 1.3). Our findings establish multiscale modeling as a powerful tool for mechanistically quantifying how pathogen biology and human social behavior shape epidemic dynamics as well as for assessing public health interventions.

Antiviral therapies such as nirmatrelvir-ritonavir are widely used for COVID-19, yet their real-world effectiveness and sources of heterogeneity in treatment response remain incompletely understood. Here, we integrate longitudinal viral load data from a large cohort of SARS-CoV-2 BA.2-infected patients in Shanghai (n=48,243) with a mechanistic within-host viral dynamics model coupled to pharmacokinetic/pharmacodynamic principles to quantify in vivo antiviral efficacy. We estimate that nirmatrelvir-ritonavir reduces viral production by approximately 55% on average. Treatment response exhibits substantial heterogeneity, with higher efficacy observed in vaccinated individuals and reduced efficacy in older adults. Sensitivity analyses demonstrate that the vaccination effect is robust across model specifications, whereas age-related differences depend on assumptions about early viral kinetics, highlighting structural identifiability challenges when analyzing sparse real-world data. These findings provide a mechanistic interpretation of heterogeneous treatment effects and establish a generalizable framework for integrating real-world clinical data with within-host models to inform antiviral optimization and personalized treatment strategies. ### Competing Interest Statement HY has received research funding from Sanofi Pasteur, Shenzhen Sanofi Pasteur Biological Products Co., Ltd, Shanghai Roche Pharmaceutical Company, and SINOVAC Biotech Ltd. None of the research funding is related to this work. ### Funding Statement This study was supported in part by the Ministry of Education, Singapore, under the Academic Research Fund Tier 1 Seed Award (RLMOE100201900000001) (to KE), a Singapore Ministry of Education Startup Grant (LKCMedicine-SUG, #022487-00001) (to KE), and Japan Science and Technology Agency (JST) PRESTO (JPMJPR23R3) (to KE). The funders had no role in the study design, data collection, data analysis, data interpretation, or writing of the manuscript. The authors and their institutions did not receive payment or services from any third party for any aspect of the submitted work beyond the stated funding. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Ethics Committee of Huashan Hospital, Fudan University gave ethical approval for this work. Written informed consent was obtained from each participant. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The data that support the findings of this study are not publicly available due to data governance and privacy restrictions but are available from the corresponding authors upon reasonable request and with permission from the data providers.

Living with COVID-19 requires continued vigilance against the spread and emergence of variants of concern (VOCs). Rapid and accurate saliva diagnostic testing, alongside basic public health responses, is a viable option contributing to effective transmission control. Nevertheless, our knowledge regarding the dynamics of SARS-CoV-2 infection in saliva is not as advanced as our understanding of the respiratory tract. Here we analyzed longitudinal viral load data of SARS-CoV-2 in saliva samples from 144 patients with mild COVID-19 (a combination of our collected data and published data). Using a mathematical model, we successfully stratified infection dynamics into three distinct groups with clear patterns of viral shedding: viral shedding durations in the three groups were 11.5 days (95% CI: 10.6 to 12.4), 17.4 days (16.6 to 18.2), and 30.0 days (28.1 to 31.8), respectively. Surprisingly, this stratified grouping remained unexplained despite our analysis of 47 types of clinical data, including basic demographic information, clinical symptoms, results of blood tests, and vital signs. Additionally, we quantified the expression levels of 92 micro-RNAs in a subset of saliva samples, but these also failed to explain the observed stratification, although the mir-1846 level may have been weakly correlated with peak viral load. Our study provides insights into SARS-CoV-2 infection dynamics in saliva, highlighting the challenges in predicting the duration of viral shedding without indicators that directly reflect an individual’s immune response, such as antibody induction. Given the significant individual heterogeneity in the kinetics of saliva viral shedding, identifying biomarker(s) for viral shedding patterns will be crucial for improving public health interventions in the era of living with COVID-19.

Defining the ever-evolving correlates of protection against symptomatic infection is critical in light of the widespread deployment of mRNA vaccines in children. Since immune maturation and exposure histories differ between children and adults, immune kinetics and correlates of protection identified in adult cohorts may not directly generalize to pediatric vaccine recipients. A prospective cohort of 5–12-year-old children (N = 70) was monitored longitudinally for 12 months after SARS-CoV-2 mRNA (BNT162b2) vaccination. Four immunological biomarkers were assessed: anti-Spike immunoglobulin G (anti-S IgG), neutralizing antibodies (nAbs), Spike-specific memory B cells (S+ MBCs), and S-reactive T cell response. We utilized mathematical models to reconstruct time-varying biomarker trajectories, while accounting for multiple immunity-conferring events (i.e., primary vaccination, breakthrough infection, and booster vaccination). Using the biomarker levels as time-varying covariates in survival analyses, we evaluated the circulating correlates of protection against symptomatic breakthrough SARS-CoV-2 infection across three post-primary vaccination periods (30 days to 3 months, 3 to 6 months, and 6 to 12 months), as an interpretable summary of early, intermediate, and late phases. We also repeated this evaluation in a global analysis without considering specific time windows. Serological markers were best described by the exponential model, while S+ MBC and T cell responses followed the inactivation model. While early protection was associated with antibodies, multivariable analyses identified T cell responses as the primary correlate of protection from 3 months onward, and this association was strongest in the presence of hybrid immunity. Under our prespecified threshold for the T cell response, the model-projected protection duration under hybrid immunity was estimated to be approximately 500 days after primary vaccination; however, empirical validation in independent cohorts will be required. Importantly, we obtained similar conclusions on the identity and direction of the correlates of protection in several sensitivity analyses adjusting for model structure, accounting for age and sex, and including asymptomatic infections. Our findings highlight the time-dependent nature of correlates of protection, emphasizing the need for employing mathematical models to reinforce the accuracy and reliability of clinical analysis so as to prevent overreliance on single-timepoint measurements of immune parameters.

Syphilis remains a major global public health challenge, particularly among men who have sex with men (MSM). Although penicillin is effective for treatment, primary prevention options are limited. Recent trials show that doxycycline post-exposure prophylaxis (doxy-PEP) can substantially reduce syphilis incidence, but its long-term population-level impact, effects on transmission dynamics and effective programme enrolment strategies remain unclear, especially when accounting real-world behavioural factors such as screening frequency, uptake, adherence and discontinuation. Here we develop a behavioural transmission-dynamic model calibrated using Bayesian methods with epidemiological and behavioural data from Singapore and England to characterize transmission dynamics in MSM, quantify the potential long-run public health impact, efficiency and robustness of alternative doxy-PEP programme enrolment strategies across different settings (for example, schools, sexual health clinics and risk groups) under varying behavioural patterns and epidemiological settings. Over 15 years, targeting MSM at high-risk (>5 partners per year) at diagnosis is most efficient (averting 2.50 (95% credible interval 0.68–5.94) and 4.60 (2.12–7.79) cases per enrolment in Singapore and England, respectively). Broader strategies to enrol all MSM attending sexual health clinics into a doxy-PEP programme achieved larger total reductions but with much lower efficiency and can avert as few as 0.02 (0.00–0.23) and 0.04 (0.01–0.46) cases per enrolment, respectively. Findings were robust across different behavioural and future scenarios. In summary, doxy-PEP programmes should prioritize enrolling MSM at high-risk diagnosed with syphilis, while maintaining frequent STI screening every 3–4 months, and monitoring the emergence or amplification of tetracycline-resistant Neisseria gonorrhoeae. A transmission model, integrating trial-derived prophylaxis efficacy and behavioural factors such as screening frequency and intervention uptake and adherence, evaluates different enrolment programmes for doxycycline post-exposure prophylaxis in terms of their potential effects on syphilis incidence, using data and indications from Singapore and England.

Viral load data provide critical insights into host-pathogen interactions and guide clinical and public health decisions. Because frequent testing is often infeasible, viral dynamics models are used to reconstruct infection trajectories, but optimal sampling strategies remain unclear. We compared two approaches for collecting SARS-CoV-2 viral load data: cross-sectional sampling (one measurement at symptom onset) and longitudinal sampling (every 3 days after onset) under constraints on the total number of tests and tests per individual. A viral dynamics model was first fitted to data from the National Basketball Association cohort, and the estimated parameters were treated as ground truth. Synthetic data were then generated under each sampling design, refitted, and evaluated for accuracy in estimating viral load over 30 days, peak viral load, peak time, and viral shedding duration. Longitudinal sampling consistently yielded lower root mean squared error and narrower one standard deviation interval than cross-sectional sampling. Peak timing and viral shedding duration were unbiased under both designs, but cross-sectional designs underestimated peak viral load and produced wider one standard deviation intervals. Coverage of viral load estimates was markedly higher for longitudinal designs (> 0.90) compared with cross-sectional ones (~0.10). Accuracy and coverage exceeded 0.96 even with just two tests per individual, with little additional benefit from more tests. In conclusion, longitudinal sampling-despite limited data-substantially improves accuracy and precision of viral load estimation compared with cross-sectional designs. These findings highlight efficient strategies for study design and resource allocation in infectious disease research.

Background:The ongoing 2023-2024 mpox outbreak in several African countries, driven by the novel Clade Ib strain, has resulted in imported cases being reported in Sweden, Thailand and India. The potential high transmissibility of this new strain and shifts in transmission modes may make territories in Asia, which were minimally affected by previous mpox waves, susceptible to community-wide transmission following importation. While this highlights the importance of early preparedness, current knowledge of the virus's transmission dynamics remains too limited to effectively inform policymaking and resource planning. Methods:A compartmental model was constructed to characterise potential mpox transmission dynamics. Importation-triggered outbreaks were simulated in 37 Asian cities under scenarios with one, three and five initial local infections. The impacts of various non-pharmaceutical interventions (NPIs), including isolation and quarantine, were projected and compared. Findings:Our simulations revealed substantial disparities in outbreak sizes among the 37 Asian cities with large-scale outbreaks expected in territories with a high proportion of sexually active individuals at risk or low immunity from smallpox vaccination. Total case counts in 1 year following initial local infections would increase linearly with initial infection size. In the scenario with three initial local infections, up to 340 cases per million residents were expected without interventions. Isolation for diagnosed cases was projected to lower the outbreak size by 43.8% (IQR: 42.7-44.5%), 67.8% (IQR: 66.5-68.9%), 80.8% (IQR: 79.5-82.0%) and 88.0% (IQR: 86.8-89.1%) when it reduced interpersonal contacts by 25%, 50%, 75% and 100%, respectively. Quarantining close contacts would contribute to a further decrease in cases of up to 22 percentage points over 1 year. Interpretation:A potential mpox outbreak in an Asian setting could be alleviated through strong surveillance and a timely response from stakeholders. NPIs are recommended for outbreak management due to their demonstrated effectiveness and practicability.

Introduction: In August 2024, the World Health Organization (WHO) declared a public health emergency due to the rapid spread of mpox in African and beyond. International travel controls (ITCs), such as health screening and viral testing, could help avoid/delay the global spread of the monkeypox virus (MPXV), fostering preparedness and response efforts. However, it is not clear whether the viral tests at immigration are sufficient to avoid importation of MPXV and which samples should be used on the viral tests. Methods: We conducted a simulation study using epidemiological and viral load data to assess the effectiveness of health screening and PCR testing at immigration. This provides estimates of the proportion of infected travelers identified with this policy. Viral dynamics models were used to estimate false-negative rates of PCR tests with different detection limits according to testing regimens at three different sites: oropharynx, saliva, and rectum. We also simulated the effects of these border control methods on the recommended duration of a monitoring period for travelers from mpox-affected regions, during which individuals would self-monitor for symptoms and practice cautionary behavior. Results: Our results show that the combination of health screening and PCR testing of saliva swabs under an endemic scenario identify only 74% of MPXV infected travelers. The use of rectal swabs combined with health screening allows the identification of a marginally larger share of infected travelers (79%) compared to saliva swabs. A similar identification rate could be achieved by using more sensitive PCR tests (detection limit [DL]: 10 copies/mL vs. 250 copies/mL used in our baseline analysis). We estimated that travelers from mpox-affected areas should monitor themselves and practice precautionary behavior for 16 days. Conclusion: Health screening and PCR testing at immigration are likely to miss a significant proportion of MPXV-infected travelers, thus a lengthy quarantine period would be required to prevent onward local transmission. Careful consideration on other factors such as economic costs and likelihood of widespread local outbreak will need to be weighed against the adoption of these measures to prevent local mpox transmission given MPXV transmissibility and severity.  ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study was supported in part by the Ministry of Education, Singapore, under its Academic Research Fund Tier 1 Seed Award (RLMOE100201900000001), a Lee Kong Chian School of Medicine startup grant (LKCMedicine-SUG, #022487-00001), and JST, PRESTO (JPMJPR23R3) (to KE). AE is supported by Japan Society for the Promotion of Science (JP22K17329) and JST (JPMJPR22R3). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The study used ONLY openly available human data that were originally located at: https://static-content.springer.com/esm/art%3A10.1038%2Fs41467-024-48754-8/MediaObjects/41467\_2024\_48754\_MOESM4\_ESM.xlsx I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced are available online at https://static-content.springer.com/esm/art%3A10.1038%2Fs41467-024-48754-8/MediaObjects/41467\_2024\_48754\_MOESM4\_ESM.xlsx [https://static-content.springer.com/esm/art%3A10.1038%2Fs41467-024-48754-8/MediaObjects/41467\_2024\_48754\_MOESM4\_ESM.xlsx][1] [1]: https://static-content.springer.com/esm/art%3A10.1038%2Fs41467-024-48754-8/MediaObjects/41467_2024_48754_MOESM4_ESM.xlsx

In-person interaction offers invaluable benefits to people. To guarantee safe in-person activities during a COVID-19 outbreak, effective identification of infectious individuals is essential. In this study, we aim to analyze the impact of screening with antigen tests in schools and workplaces on identifying COVID-19 infections. We assess the effectiveness of various screening test strategies with antigen tests in schools and workplaces through quantitative simulations. The primary outcome of our analyses is the proportion of infected individuals identified. The transmission process at the population level is modeled using a deterministic compartmental model. Infected individuals are identified through screening tests or symptom development. The time-varying sensitivity of antigen tests and infectiousness is determined by a viral dynamics model. Screening test strategies are characterized by the screening schedule, sensitivity of antigen tests, screening duration, timing of screening initiation, and available tests per person. Here, we show that early and frequent screening is the key to maximizing the effectiveness of the screening program. For example, 44.5% (95% CI: 40.8–47.5) of infected individuals are identified by daily testing, whereas it is only 33.7% (95% CI: 30.5–37.3) when testing is performed at the end of the program duration. If high sensitivity antigen tests (Detection limit: $$6.3\times {10}^{4}$$ copies/mL) are deployed, it reaches 69.3% (95% CI: 66.5–72.5). High sensitivity antigen tests, high frequency screening tests, and immediate initiation of screening tests are important to safely restart educational and economic activities in-person. Our computational framework is useful for assessing screening programs by incorporating situation-specific factors. During the COVID-19 pandemic, people actively sought safer ways to resume in-person educational and economic activities while keeping the risk of infection low. For this, it may have been key to implement regular screening tests for individuals in places like schools and workplaces, since these tests can identify positive cases and help prevent the spread of the virus within these settings. Here, we introduce a computer model that evaluates the effectiveness of different screening programs in those facilities. The model involves how the virus spreads between people and within the human body, considering how the accuracy of tests can change as the infection progresses. The study examines various screening strategies. The simulations demonstrate that using highly sensitive tests, conducting frequent screenings, and starting the tests immediately are crucial for effectively identifying positive cases. Our approach can be flexibly expanded in the future to consider various factors like vaccination and new variants. Jeong, Ejima and Kim et al. assess the effectiveness of various screening strategies with antigen tests for COVID-19 infections in schools and workplaces. A computational framework is employed to determine the best strategies while considering factors such as within-host viral dynamics, transmissions, screening schedules and test sensitivity.

Nutrition epidemiological models involve many analytic decisions, such as defining exposures, selecting which covariates to include, or configuring variables in different ways. We explored the impact of analytical decisions on conclusions in nutrition epidemiology using self-reported beef intake and incident coronary heart disease as a case study. We used REasons for Geographic and Racial Differences in Stroke (REGARDS) data, and selected covariates and their configurations from published literature to recapitulate common models used to assess associations between meat intake and health outcomes. Three model sets were designed: sets one and two used continuous and quintile-defined beef intakes, respectively, each with ∼500,000 randomly sampled specifications. Set three models directly emulated published covariate combinations. Few models (<1%) were statistically significant at p < 0.05. More hazard ratio (HR) point estimates were >1 when beef was polychotomized via quintiles (95% of models) vs. continuous intake (79% of models). Including covariates for race or multivitamin use shifted HRs toward the null with similar confidence interval widths. Models emulating existing published associations were all above HR of 1. For our case study, exposure configuration and exposure inclusion resulted in substantially different HR distributions, illustrating how analytical decisions can affect nutrition-related exposure/outcome associations. The finding of few statistically significant models does not prove, but may suggest, minimal association between beef and CHD. Singular assessments of nutritional epidemiology questions should therefore be interpreted with caution. Modeling many analytical approaches may better establish and investigate the uncertainty of nutritional epidemiology questions and provisional answers.

Initial investigation into the emerging mpox outbreak of novel clade Ib in eastern Democratic Republic of the Congo has identified signs of sustained human-to-human transmission and epidemiological links to sexual contacts involving female sex workers (FSWs)1, which have not been observed in previous clade Ia outbreaks. Using mathematical models incorporating age-dependent contact patterns, we quantified the role of frequent sexual interactions as opposed to community contacts in clade Ib's dynamics and found that this additional mode of transmission could explain its increased outbreak potential compared with clade Ia. As with the globally-circulating clade IIb, transmitted predominantly among men who have sex with men2, our findings reinforce the importance of protecting key population groups, specifically FSWs for clade Ib, in controlling ongoing mpox outbreaks.

In the absence of effective pharmaceutical interventions early in an infectious disease outbreak, non-pharmaceutical measures, especially isolating infected individuals, critically limit its impact. The ongoing COVID-19 pandemic has sparked debates on optimal isolation guidelines. This study proposes a variable isolation period approach (variable-period approach), tailoring isolation durations for distinct population groups with varied viral load dynamics. To compare our variable-period approach with a fixed-period strategy, we developed a simulation model generating synthetic longitudinal SARS-CoV-2 viral load data. The data was generated from the viral dynamics model parameterized using SARS-CoV-2 Delta patient data in Singapore, accounting for age and vaccination status. Findings show that age and vaccination status significantly influence viral dynamics, with younger age and vaccination linked to shorter viral shedding durations. The variable-period framework suggests longer isolation lengths for older and unvaccinated individuals. By setting the leaking risk (risk of remaining infectious at the end of isolation) below 10%, the optimal fixed-period isolation is 14 days, with an average excess isolation burden of 7.4 unnecessary days. In contrast, the variable-period guideline reduces the excess isolation burden to 6.0 days, with the optimal isolation periods ranging from 9 to 16 days, depending on the population group. We confirmed similar results when we used the effective reproduction number as an alternative to the leaking risk. In this case, study using the SARS-CoV-2 Delta variant, our analysis demonstrates that unnecessary time spent in isolation can be reduced by adopting variable-period guidelines based on patient characteristics. The isolation of infected patients is crucial in minimizing the impact of a pandemic. Nevertheless, it can significantly burden the patients themselves. Therefore, guidelines for isolation should be established to decrease unnecessary isolation periods, without relying solely on viral tests. Here, we introduce a protocol to evaluate guidelines with fixed and variable isolation periods. Our analysis revealed that adjusting isolation lengths based on age and vaccination status, rather than enforcing a uniform period for all patients, can reduce the necessary isolation period by 1.4 to 1.8 days per person on average. Customizing the isolation period according to patient characteristics is justified to decrease the duration of redundant isolation, concurrently mitigating the risk of further transmission. Ejima et al. introduce a computational protocol to evaluate isolation guidelines, showing that adjusting isolation durations based on age and vaccination status reduces unnecessary isolation by 1.4 to 1.8 days per person while maintaining safety. Tailored isolation periods minimize redundant isolation and mitigate transmission risks.

Understanding the dynamics of SARS-CoV-2 antibody levels post-booster vaccination is important to inform their durations of protection. Longitudinal antibody data was collected on the day of booster vaccination, as well as 28, 180, and 360 days after. Using nonlinear mixed effects models, we mapped the kinetics of binding IgA and IgG against wild-type (WT) and Omicron BA.1 spike proteins. Furthermore, we analyzed the association between antibody levels and risk of SARS-CoV-2 vaccine breakthrough infection through survival analyzes, and predicted durations of protection against infection. We found that the antibody response waned more rapidly following the Pfizer/BioNTech BNT162b2 booster compared to the Moderna mRNA-1273 booster. However, individuals boosted with the Pfizer vaccine exhibited a steeper rebound in antibody levels after infection. Faster postinfection antibody growth rates were observed in the elderly, females, and those with late infections. High antibody levels for WT IgG and BA.1 IgA at day 28 post-booster were associated with reduced infection risk; hazard ratios were 0.47 (95% CI [0.22, 0.98]) and 0.36 (95% CI [0.17, 0.78]), respectively, compared to low levels. Time-varying antibody levels showed better survival model fits. At medium COVID-19 case incidence (621 cases per million per day), a binding BA.1 IgA response of at least 20% is needed to sustain 80% protection against infection over 155 days post-booster. Our estimates of protection durations against SARS-CoV-2 infection post-booster vaccination may help inform the ideal frequency of boosters.

Mathematical models of viral dynamics are crucial in understanding infection trajectories. However, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral load data often includes limited sparse observations with significant heterogeneity. This study aims to: (1) understand the impact of patient characteristics in shaping the temporal viral load trajectory and (2) establish a data collection protocol (DCP) to reliably reconstruct individual viral load trajectories. We collected longitudinal viral load data for SARS-CoV-2 Delta and Omicron variants from 243 patients in Singapore (2021-2022). A viral dynamics model was calibrated using patients' age, symptom presence, and vaccination status. We accessed associations between these patient characteristics and aspects of viral dynamics using linear regression models. We evaluated the accuracy of viral load trajectory estimation under different simulated DCPs by varying patient numbers, test frequencies, and test intervals. Older unvaccinated individuals had a longer viral shedding duration due to lower infection and cell death rates. Higher peak viral loads were found in older, symptomatic, and vaccinated individuals, with earlier peaks in younger vaccinated individuals. Symptom presence and vaccination resulted in a shorter time from infection to diagnosis. To accurately estimate viral dynamics, more frequent tests, longer test intervals, and larger patient samples are required. For 500 patients, a 21-day follow-up with measurements every 3 days and an 8-day follow-up with daily measurements was optimal for the Delta and Omicron variants, respectively. Patient characteristics significantly impacted viral dynamics. Our analytic approach and recommended DCPs can enhance preparedness and response to emerging pathogens beyond SARS-CoV-2.

In August 2024, the World Health Organization (WHO) declared a public health emergency due to the rapid spread of mpox in Africa and beyond. International travel controls (ITCs), such as health screening and viral testing, could help avoid/delay the global spread of MPXV, fostering preparedness and response efforts. However, it is not clear whether the viral tests at immigration are sufficient to avoid introduction of MPXV and which samples should be used on the viral tests. We conducted a simulation study using epidemiological and viral load data to assess the effectiveness of health screening and polymerase chain reaction (PCR) testing at immigration. The primary outcome was the proportion of MPXV-infected travelers identified under various international travel control policies. To estimate time-varying false-negative rates of PCR tests with different detection limits, we employed viral dynamics models calibrated to data from three anatomical sites: oropharynx, saliva, and rectum. Additionally, we simulated the effects of these control measures on the recommended duration of a post-entry monitoring period. Travelers were assumed to depart from mpox-affected countries, defined as those with ongoing MPXV transmission, potentially representing both historically endemic regions and countries with recent outbreaks. Our results show that under an endemic scenario, the combination of health screening and PCR testing using saliva swabs identifies approximately 74

In the early COVID-19 pandemic, the strain on healthcare facilities highlighted the need for reliable biomarkers to predict progression to severe COVID-19. Neutrophils, the most abundant leukocytes in circulation, are early defenders against pathogens. In a Singaporean adult cohort, early neutrophil mediators were assessed for their suitability as prognostic biomarkers of COVID-19 complications. Plasma levels of myeloperoxidase, elastase, soluble urokinase plasminogen activator receptor (suPAR) and soluble suppressor of tumorigenicity 2 (sST2) in 35 non-severe and 14 severe cases were measured twice, 2-7 days apart after hospitalisation. Nineteen controls were included. The levels of MPO, elastase, suPAR and sST2 were significantly higher in patients with severe COVID-19 compared to those with mild and healthy controls. At baseline sampling, MPO and suPAR predicted severe COVID-19 and had AUROCs of 0.76 and 0.87, respectively. MPO and suPAR at cut-off values of 26.41 ng/ml and 3.19 ng/ml, respectively showed approximately 71% sensitivity and 81 - 84% specificity to differentiate severe COVID-19. In contrast, elastase and neutrophil counts were less predictive of severe disease. In adult COVID-19, MPO and suPAR may be reliable prognostic biomarkers of severe disease during acute COVID-19. Further validation of these markers in a larger cohort and in other infectious diseases is warranted.