Bayesian nonparametric inference for heterogeneously mixing infectious disease models.

SignificanceMathematical models of infectious disease transmission continue to play a vital role in understanding, mitigating, and preventing outbreaks. The vast majority of epidemic models in the literature are parametric, meaning that they contain inherent assumptions about how transmission occurs in a population. However, such assumptions can be lacking in appropriate biological or epidemiological justification and in consequence lead to erroneous scientific conclusions and misleading predictions. We propose a flexible Bayesian nonparametric framework that avoids the need to make strict model assumptions about the infection process and enables a far more data-driven modeling approach for inferring the mechanisms governing transmission. We use our methods to enhance our understanding of the transmission mechanisms of the 2001 UK foot and mouth disease outbreak.

Comparing Contact Tracing Through Bluetooth and GPS Surveillance Data: Simulation-Driven Approach.

BACKGROUND: Accurate and responsive epidemiological simulations of epidemic outbreaks inform decision-making to mitigate the impact of pandemics. These simulations must be grounded in quantities derived from measurements, among which the parameters associated with contacts between individuals are notoriously difficult to estimate. Digital contact tracing data, such as those provided by Bluetooth beaconing or GPS colocating, can provide more precise measures of contact than traditional methods based on direct observation or self-reporting. Both measurement modalities have shortcomings and are prone to false positives or negatives, as unmeasured environmental influences bias the data. OBJECTIVE: We aim to compare GPS colocated versus Bluetooth beacon-derived proximity contact data for their impacts on transmission models' results under community and types of diseases. METHODS: We examined the contact patterns derived from 3 data sets collected in 2016, with participants comprising students and staff from the University of Saskatchewan in Canada. Each of these 3 data sets used both Bluetooth beaconing and GPS localization on smartphones running the Ethica Data (Avicenna Research) app to collect sensor data about every 5 minutes over a month. We compared the structure of contact networks inferred from proximity contact data collected with the modalities of GPS colocating and Bluetooth beaconing. We assessed the impact of sensing modalities on the simulation results of transmission models informed by proximate contacts derived from sensing data. Specifically, we compared the incidence number, attack rate, and individual infection risks across simulation results of agent-based susceptible-exposed-infectious-removed transmission models of 4 different contagious diseases. We have demonstrated their differences with violin plots, 2-tailed t tests, and Kullback-Leibler divergence. RESULTS: Both network structure analyses show visually salient differences in proximity contact data collected between GPS colocating and Bluetooth beaconing, regardless of the underlying population. Significant differences were found for the estimated attack rate based on distance threshold, measurement modality, and simulated disease. This finding demonstrates that the sensor modality used to trace contact can have a significant impact on the expected propagation of a disease through a population. The violin plots of attack rate and Kullback-Leibler divergence of individual infection risks demonstrated discernible differences for different sensing modalities, regardless of the underlying population and diseases. The results of the t tests on attack rate between different sensing modalities were mostly significant (P<.001). CONCLUSIONS: We show that the contact networks generated from these 2 measurement modalities are different and generate significantly different attack rates across multiple data sets and pathogens. While both modalities offer higher-resolution portraits of contact behavior than is possible with most traditional contact measures, the differential impact of measurement modality on the simulation outcome cannot be ignored and must be addressed in studies only using a single measure of contact in the future.

Application of mathematical modelling to inform national malaria intervention planning in Nigeria.

BACKGROUND: For their 2021-2025 National Malaria Strategic Plan (NMSP), Nigeria's National Malaria Elimination Programme (NMEP), in partnership with the World Health Organization (WHO), developed a targeted approach to intervention deployment at the local government area (LGA) level as part of the High Burden to High Impact response. Mathematical models of malaria transmission were used to predict the impact of proposed intervention strategies on malaria burden. METHODS: An agent-based model of Plasmodium falciparum transmission was used to simulate malaria morbidity and mortality in Nigeria's 774 LGAs under four possible intervention strategies from 2020 to 2030. The scenarios represented the previously implemented plan (business-as-usual), the NMSP at an 80% or higher coverage level and two prioritized plans according to the resources available to Nigeria. LGAs were clustered into 22 epidemiological archetypes using monthly rainfall, temperature suitability index, vector abundance, pre-2010 parasite prevalence, and pre-2010 vector control coverage. Routine incidence data were used to parameterize seasonality in each archetype. Each LGA's baseline malaria transmission intensity was calibrated to parasite prevalence in children under the age of five years measured in the 2010 Malaria Indicator Survey (MIS). Intervention coverage in the 2010-2019 period was obtained from the Demographic and Health Survey, MIS, the NMEP, and post-campaign surveys. RESULTS: Pursuing a business-as-usual strategy was projected to result in a 5% and 9% increase in malaria incidence in 2025 and 2030 compared with 2020, while deaths were projected to remain unchanged by 2030. The greatest intervention impact was associated with the NMSP scenario with 80% or greater coverage of standard interventions coupled with intermittent preventive treatment in infants and extension of seasonal malaria chemoprevention (SMC) to 404 LGAs, compared to 80 LGAs in 2019. The budget-prioritized scenario with SMC expansion to 310 LGAs, high bed net coverage with new formulations, and increase in effective case management rate at the same pace as historical levels was adopted as an adequate alternative for the resources available. CONCLUSIONS: Dynamical models can be applied for relative assessment of the impact of intervention scenarios but improved subnational data collection systems are required to allow increased confidence in predictions at sub-national level.

Public health impact and cost effectiveness of routine and catch-up vaccination of girls and women with a nine-valent HPV vaccine in Japan: a model-based study.

BACKGROUND: Combined with cancer screening programs, vaccination against human papillomavirus (HPV) can significantly reduce the high health and economic burden of HPV-related disease in Japan. The objective of this study was to assess the health impact and cost effectiveness of routine and catch-up vaccination of girls and women aged 11-26 years with a 4-valent (4vHPV) or 9-valent HPV (9vHPV) vaccine in Japan compared with no vaccination. METHODS: We used a mathematical model adapted to the population and healthcare settings in Japan. We compared no vaccination and routine vaccination of 12-16-year old girls with 1) 4vHPV vaccine, 2) 9vHPV vaccine, and 3) 9vHPV vaccine in addition to a temporary catch-up vaccination of 17-26 years old girls and women with 9vHPV. We estimated the expected number of disease cases and deaths, discounted (at 2% per year) future costs (in 2020 ¥) and discounted quality-adjusted life years (QALY), and incremental cost effectiveness ratios (ICER) of each strategy over a time horizon of 100 years. To test the robustness of the conclusions, we conducted scenario and sensitivity analyses. RESULTS: Over 100 years, compared with no vaccination, 9vHPV vaccination was projected to reduce the incidence of 9vHPV-related cervical cancer by 86% (from 15.24 new cases per 100,000 women in 2021 to 2.02 in 2121). A greater number of cervical cancer cases (484,248) and cancer-related deaths (50,102) were avoided through the described catch-up vaccination program. Routine HPV vaccination with 4vHPV or 9vHPV vaccine prevented 5,521,000 cases of anogenital warts among women and men. Around 23,520 and 21,400 diagnosed non-cervical cancers are prevented by catch-up vaccination among women and men, respectively. Compared with no vaccination, the ICER of 4vHPV vaccination was ¥975,364/QALY. Compared to 4vHPV, 9vHPV + Catch-up had an ICER of ¥1,534,493/QALY. CONCLUSIONS: A vaccination program with a 9-valent vaccine targeting 12 to 16 year-old girls together with a temporary catchup program will avert significant numbers of cases of HPV-related diseases among both men and women. Furthermore, such a program was the most cost effective among the vaccination strategies we considered, with an ICER well below a threshold of ¥5000,000/QALY.

Forecasting the 2017/2018 seasonal influenza epidemic in England using multiple dynamic transmission models: a case study.

BACKGROUND: Since the 2009 A/H1N1 pandemic, Public Health England have developed a suite of real-time statistical models utilising enhanced pandemic surveillance data to nowcast and forecast a future pandemic. Their ability to track seasonal influenza and predict heightened winter healthcare burden in the light of high activity in Australia in 2017 was untested. METHODS: Four transmission models were used in forecasting the 2017/2018 seasonal influenza epidemic in England: a stratified primary care model using daily, region-specific, counts and virological swab positivity of influenza-like illness consultations in general practice (GP); a strain-specific (SS) model using weekly, national GP ILI and virological data; an intensive care model (ICU) using reports of ICU influenza admissions; and a synthesis model that included all data sources. For the first 12 weeks of 2018, each model was applied to the latest data to provide estimates of epidemic parameters and short-term influenza forecasts. The added value of pre-season population susceptibility data was explored. RESULTS: The combined results provided valuable nowcasts of the state of the epidemic. Short-term predictions of burden on primary and secondary health services were initially highly variable before reaching consensus beyond the observed peaks in activity between weeks 3-4 of 2018. Estimates for R0 were consistent over time for three of the four models until week 12 of 2018, and there was consistency in the estimation of R0 across the SPC and SS models, and in the ICU attack rates estimated by the ICU and the synthesis model. Estimation and predictions varied according to the assumed levels of pre-season immunity. CONCLUSIONS: This exercise successfully applied a range of pandemic models to seasonal influenza. Forecasting early in the season remains challenging but represents a crucially important activity to inform planning. Improved knowledge of pre-existing levels of immunity would be valuable.

Multiple system atrophy prions retain strain specificity after serial propagation in two different Tg(SNCA*A53T) mouse lines.

Previously, we reported that intracranial inoculation of brain homogenate from multiple system atrophy (MSA) patient samples produces neurological disease in the transgenic (Tg) mouse model TgM83+/-, which uses the prion protein promoter to express human α-synuclein harboring the A53T mutation found in familial Parkinson's disease (PD). In our studies, we inoculated MSA and control patient samples into Tg mice constructed using a P1 artificial chromosome to express wild-type (WT), A30P, and A53T human α-synuclein on a mouse α-synuclein knockout background [Tg(SNCA+/+)Nbm, Tg(SNCA*A30P+/+)Nbm, and Tg(SNCA*A53T+/+)Nbm]. In contrast to studies using TgM83+/- mice, motor deficits were not observed by 330-400 days in any of the Tg(SNCA)Nbm mice after inoculation with MSA brain homogenates. However, using a cell-based bioassay to measure α-synuclein prions, we found brain homogenates from Tg(SNCA*A53T+/+)Nbm mice inoculated with MSA patient samples contained α-synuclein prions, whereas control mice did not. Moreover, these α-synuclein aggregates retained the biological and biochemical characteristics of the α-synuclein prions in MSA patient samples. Intriguingly, Tg(SNCA*A53T+/+)Nbm mice developed α-synuclein pathology in neurons and astrocytes throughout the limbic system. This finding is in contrast to MSA-inoculated TgM83+/- mice, which develop exclusively neuronal α-synuclein aggregates in the hindbrain that cause motor deficits with advanced disease. In a crossover experiment, we inoculated TgM83+/- mice with brain homogenate from two MSA patient samples or one control sample first inoculated, or passaged, in Tg(SNCA*A53T+/+)Nbm animals. Additionally, we performed the reverse experiment by inoculating Tg(SNCA*A53T+/+)Nbm mice with brain homogenate from the same two MSA samples and one control sample first passaged in TgM83+/- animals. The TgM83+/- mice inoculated with mouse-passaged MSA developed motor dysfunction and α-synuclein prions, whereas the mouse-passaged control sample had no effect. Similarly, the mouse-passaged MSA samples induced α-synuclein prion formation in Tg(SNCA*A53T+/+)Nbm mice, but the mouse-passaged control sample did not. The confirmed transmission of α-synuclein prions to a second synucleinopathy model and the ability to propagate prions between two distinct mouse lines while retaining strain-specific properties provides compelling evidence that MSA is a prion disease.

MSA prions exhibit remarkable stability and resistance to inactivation.

In multiple system atrophy (MSA), progressive neurodegeneration results from the protein α-synuclein misfolding into a self-templating prion conformation that spreads throughout the brain. MSA prions are transmissible to transgenic (Tg) mice expressing mutated human α-synuclein (TgM83+/-), inducing neurological disease following intracranial inoculation with brain homogenate from deceased patient samples. Noting the similarities between α-synuclein prions and PrP scrapie (PrPSc) prions responsible for Creutzfeldt-Jakob disease (CJD), we investigated MSA transmission under conditions known to result in PrPSc transmission. When peripherally exposed to MSA via the peritoneal cavity, hind leg muscle, and tongue, TgM83+/- mice developed neurological signs accompanied by α-synuclein prions in the brain. Iatrogenic CJD, resulting from PrPSc prion adherence to surgical steel instruments, has been investigated by incubating steel sutures in contaminated brain homogenate before implantation into mouse brain. Mice studied using this model for MSA developed disease, whereas wire incubated in control homogenate had no effect on the animals. Notably, formalin fixation did not inactivate α-synuclein prions. Formalin-fixed MSA patient samples also transmitted disease to TgM83+/- mice, even after incubating in fixative for 244 months. Finally, at least 10% sarkosyl was found to be the concentration necessary to partially inactivate MSA prions. These results demonstrate the robustness of α-synuclein prions to denaturation. Moreover, they establish the parallel characteristics between PrPSc and α-synuclein prions, arguing that clinicians should exercise caution when working with materials that might contain α-synuclein prions to prevent disease.

A systematic review of transmission dynamic studies of methicillin-resistant Staphylococcus aureus in non-hospital residential facilities.

BACKGROUND: Non-hospital residential facilities are important reservoirs for MRSA transmission. However, conclusions and public health implications drawn from the many mathematical models depicting nosocomial MRSA transmission may not be applicable to these settings. Therefore, we reviewed the MRSA transmission dynamics studies in defined non-hospital residential facilities to: (1) provide an overview of basic epidemiology which has been addressed; (2) identify future research direction; and (3) improve future model implementation. METHODS: A review was conducted by searching related keywords in PUBMED without time restriction as well as internet searches via Google search engine. We included only articles describing the epidemiological transmission pathways of MRSA/community-associated MRSA within and between defined non-hospital residential settings. RESULTS: Among the 10 included articles, nursing homes (NHs) and correctional facilities (CFs) were two settings considered most frequently. Importation of colonized residents was a plausible reason for MRSA outbreaks in NHs, where MRSA was endemic without strict infection control interventions. The importance of NHs over hospitals in increasing nosocomial MRSA prevalence was highlighted. Suggested interventions in NHs included: appropriate staffing level, screening and decolonizing, and hand hygiene. On the other hand, the small population amongst inmates in CFs has no effect on MRSA community transmission. Included models ranged from system-level compartmental models to agent-based models. There was no consensus over the course of disease progression in these models, which were mainly featured with NH residents /CF inmates/ hospital patients as transmission pathways. Some parameters used by these models were outdated or unfit. CONCLUSIONS: Importance of NHs has been highlighted from these current studies addressing scattered aspects of MRSA epidemiology. However, the wide variety of non-hospital residential settings suggest that more work is needed before robust conclusions can be drawn. Learning from existing work for hospitals, we identified critical future research direction in this area from infection control, ecological and economic perspectives. From current model deficiencies, we suggest more transmission pathways be specified to depict MRSA transmission, and further empirical studies be stressed to support evidence-based mathematical models of MRSA in non-hospital facilities. Future models should be ready to cope with the aging population structure.

Models and analyses to understand threats to polio eradication.

To achieve complete polio eradication, the live oral poliovirus vaccine (OPV) currently used must be phased out after the end of wild poliovirus transmission. However, poorly understood threats may arise when OPV use is stopped. To counter these threats, better models than those currently available are needed. Two articles recently published in BMC Medicine address these issues. Mercer et al. (BMC Med 15:180, 2017) developed a statistical model analysis of polio case data and characteristics of cases occurring in several districts in Pakistan to inform resource allocation decisions. Nevertheless, despite having the potential to accelerate the elimination of polio cases, their analyses are unlikely to advance our understanding OPV cessation threats. McCarthy et al. (BMC Med 15:175, 2017) explored one such threat, namely the emergence and transmission of serotype 2 circulating vaccine derived poliovirus (cVDPV2) after OPV2 cessation, and found that the risk of persistent spread of cVDPV2 to new areas increases rapidly 1-5 years after OPV2 cessation. Thus, recently developed models and analysis methods have the potential to guide the required steps to surpass these threats. 'Big data' scientists could help with this; however, datasets covering all eradication efforts should be made readily available.Please see related articles: https://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-017-0937-y and https://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-017-0941-2 .

Impact and Cost-effectiveness of 3 Doses of 9-Valent Human Papillomavirus (HPV) Vaccine Among US Females Previously Vaccinated With 4-Valent HPV Vaccine.

BACKGROUND: We estimated the potential impact and cost-effectiveness of providing 3-doses of nonavalent human papillomavirus (HPV) vaccine (9vHPV) to females aged 13-18 years who had previously completed a series of quadrivalent HPV vaccine (4vHPV), a strategy we refer to as "additional 9vHPV vaccination." METHODS: We used 2 distinct models: (1) the simplified model, which is among the most basic of the published dynamic HPV models, and (2) the US HPV-ADVISE model, a complex, stochastic, individual-based transmission-dynamic model. RESULTS: When assuming no 4vHPV cross-protection, the incremental cost per quality-adjusted life-year (QALY) gained by additional 9vHPV vaccination was $146 200 in the simplified model and $108 200 in the US HPV-ADVISE model ($191 800 when assuming 4vHPV cross-protection). In 1-way sensitivity analyses in the scenario of no 4vHPV cross-protection, the simplified model results ranged from $70 300 to $182 000, and the US HPV-ADVISE model results ranged from $97 600 to $118 900. CONCLUSIONS: The average cost per QALY gained by additional 9vHPV vaccination exceeded $100 000 in both models. However, the results varied considerably in sensitivity and uncertainty analyses. Additional 9vHPV vaccination is likely not as efficient as many other potential HPV vaccination strategies, such as increasing primary 9vHPV vaccine coverage.

Modeling individual heterogeneity in the acquisition of recurrent infections: an application to parvovirus B19.

In recent years, it has been shown that individual heterogeneity in the acquisition of infectious diseases has a large impact on the estimation of important epidemiological parameters such as the (basic) reproduction number. Therefore, frailty modeling has become increasingly popular in infectious disease epidemiology. However, so far, using frailty models, it was assumed infections confer lifelong immunity after recovery, an assumption which is untenable for non-immunizing infections. Our work concentrates on refining the existing frailty models to encompass complexities of waning immunity and consequently recurrent infections while accounting for individual heterogeneity. Univariate and shared gamma frailty models, frequently used in practice, and correlated gamma frailty models that have proven to be a valuable alternative are considered. We show that incorrectly assuming lifelong immunity when applying frailty models introduces substantial bias in the estimation of both the baseline hazard and the frailty parameters, and consequently of the basic and effective reproduction number. We illustrate our work using cross-sectional serological data on parvovirus B19 (PVB19) from Belgium for which the link with varicella zoster virus is exploited.

Too late to vaccinate? The incremental benefits and cost-effectiveness of a delayed catch-up program using the 4-valent human papillomavirus vaccine in Norway.

BACKGROUND: Human papillomavirus (HPV) vaccines are ideally administered before HPV exposure; therefore, catch-up programs for girls past adolescence have not been readily funded. We evaluated the benefits and cost-effectiveness of a delayed, 1-year female catch-up vaccination program in Norway. METHODS: We calibrated a dynamic HPV transmission model to Norwegian data and projected the costs and benefits associated with 8 HPV-related conditions while varying the upper vaccination age limit to 20, 22, 24, or 26 years. We explored the impact of vaccine protection in women with prior vaccine-targeted HPV infections, vaccine cost, coverage, and natural- and vaccine-induced immunity. RESULTS: The incremental benefits and cost-effectiveness decreased as the upper age limit for catch-up increased. Assuming a vaccine cost of $150/dose, vaccination up to age 20 years remained below Norway's willingness-to-pay threshold (approximately $83 000/quality-adjusted life year gained); extension to age 22 years was cost-effective at a lower cost per dose ($50-$75). At high levels of vaccine protection in women with prior HPV exposure, vaccinating up to age 26 years was cost-effective. Results were stable with lower coverage. CONCLUSIONS: HPV vaccination catch-up programs, 5 years after routine implementation, may be warranted; however, even at low vaccine cost per dose, the cost-effectiveness of vaccinating beyond age 22 years remains uncertain.

Transmission Models of Historical Ebola Outbreaks.

To guide the collection of data under emergent epidemic conditions, we reviewed compartmental models of historical Ebola outbreaks to determine their implications and limitations. We identified future modeling directions and propose that the minimal epidemiologic dataset for Ebola model construction comprises duration of incubation period and symptomatic period, distribution of secondary cases by infection setting, and compliance with intervention recommendations.

Models of marine molluscan diseases: Trends and challenges.

Disease effects on host population dynamics and the transmission of pathogens between hosts are two important challenges for understanding how epizootics wax and wane and how disease influences host population dynamics. For the management of marine shellfish resources, marine diseases pose additional challenges in early intervention after the appearance of disease, management of the diseased population to limit a decline in host abundance, and application of measures to restrain that decline once it occurs. Mathematical models provide one approach for quantifying these effects and addressing the competing goals of managing the diseased population versus managing the disease. The majority of models for molluscan diseases fall into three categories distinguished by these competing goals. (1) Models that consider disease effects on the host population tend to focus on pathogen proliferation within the host. Many of the well-known molluscan diseases are pandemic, in that they routinely reach high prevalence rapidly over large geographic expanses, are characterized by transmission that does not depend upon a local source, and exert a significant influence on host population dynamics. Models focused on disease proliferation examine the influence of environmental change on host population metrics and provide a basis to better manage diseased stocks. Such models are readily adapted to questions of fishery management and habitat restoration. (2) Transmission models are designed to understand the mechanisms triggering epizootics, identify factors impeding epizootic development, and evaluate controls on the rate of disease spread over the host's range. Transmission models have been used extensively to study terrestrial diseases, yet little attention has been given to their potential for understanding the epidemiology of marine molluscan diseases. For management of diseases of wild stocks, transmission models open up a range of options, including the application of area management, manipulation of host abundance, and use of scavengers and filter feeders to limit the concentration of infective particles. (3) The details of host population processes and pathogen transmission dynamics are blended in models that evaluate the effects of natural selection and/or genetic modification in developing disease resistance in the host population. Application of gene-based models to marine diseases is only now beginning and represents a promising approach that may provide a mechanistic basis for managing marine diseases and their host populations. Overall disease models remain both uncommon and underutilized in addressing the needs for managing molluscan diseases and their host populations.

Structured Literature Review to Identify Human Papillomavirus's Natural History Parameters for Dynamic Population Models of Vaccine Impacts.

Human papillomavirus (HPV) is a common sexually transmitted virus that can cause cervical cancer and other diseases. Dynamic transmission models (DTMs) have been developed to evaluate the health and economic impacts of HPV vaccination. These models typically include many parameters, such as natural history of the disease, transmission, demographic, behavioral, and screening. To ensure the accuracy of DTM projections, it is important to parameterize them with the best available evidence. This study aimed to identify and synthesize data needed to parametrize DTMs on the natural history of HPV infection and related diseases. Parameters describing data of interest were grouped by their anatomical location (genital warts, recurrent respiratory papillomatosis, and cervical, anal, vaginal, vulvar, head and neck, and penile cancers), and natural history (progression, regression, death, cure, recurrence, detection), and were identified through a systematic literature review (SLR) and complementary targeted literature reviews (TLRs). The extracted data were then synthesized by pooling parameter values across publications, and summarized using the range of values across studies reporting each parameter and the median value from the most relevant study. Data were extracted and synthesized from 223 studies identified in the SLR and TLRs. Parameters frequently reported pertained to cervical cancer outcomes, while data for other anatomical locations were less available. The synthesis of the data provides a large volume of parameter values to inform HPV DTMs, such as annual progression rates from cervical intraepithelial neoplasia (CIN) 1 to CIN 2+ (median of highest quality estimate 0.0836), CIN 2 to CIN 3+ (0.0418), carcinoma in situ (CIS) 2 to local cancer+ (0.0396), and regional to distant cancer (0.0474). Our findings suggest that while there is a large body of evidence on cervical cancer, parameter values featured substantial heterogeneity across studies, and further studies are needed to better parametrize the non-cervical components of HPV DTMs.

A Systematic Review of Mathematical Models of Dengue Transmission and Vector Control: 2010-2020.

Vector control methods are considered effective in averting dengue transmission. However, several factors may modify their impact. Of these controls, chemical methods, in the long run, may increase mosquitoes' resistance to chemicides, thereby decreasing control efficacy. The biological methods, which may be self-sustaining and very effective, could be hampered by seasonality or heatwaves (resulting in, e.g., loss of Wolbachia infection). The environmental methods that could be more effective than the chemical methods are under-investigated. In this study, a systematic review is conducted to explore the present understanding of the effectiveness of vector control approaches via dengue transmission models.

A novel method to jointly estimate transmission rate and decay rate parameters in environmental transmission models.

In environmental transmission, pathogens transfer from one individual to another via the environment. It is a common transmission mechanism in a wide range of host-pathogen systems. Incorporating environmental transmission in dynamic transmission models is crucial for gauging the effect of interventions, as extrapolating model results to new situations is only valid when the mechanisms are modelled correctly. The challenge in environmental transmission models lies in not jointly identifiable parameters for pathogen shedding, decay, and transmission dynamics. To solve this unidentifiability issue, we present a stochastic environmental transmission model with a novel scaling method for shedding rate parameter and a novel estimation method that distinguishes transmission rate and decay rate parameters. The core of our scaling and estimation method is calculating exposure and relating exposure to infection risks. By scaling shedding rate parameter, we standardize exposure to pathogens contributed by one infectious individual present during one time interval to one. The standardized exposure leads to a standard definition of transmission rate parameter applicable to scenarios with different decay rate parameters. Hence, we unify direct transmission (large decay rate) and environmental transmission in a continuous manner. More importantly, our exposure-based estimation method can correctly estimate back the transmission rate and the decay rate parameters, while the commonly used trajectory-based method failed. The reason is that exposure-based method gives the correct weight to infection data from previous observation periods. The correct estimation from exposure-based method will lead to more reliable predictions of intervention impact. Using the effect of disinfection as an example, we show how incorrectly estimated parameters may lead to incorrect conclusions about the effectiveness of interventions. This illustrates the importance of correct estimation of transmission rate and decay rate parameters for extrapolating environmental transmission models and predicting intervention effects.

Health impact and cost effectiveness of implementing gender-neutral HPV vaccination in Japan.

OBJECTIVE: To assess the public health impact and cost effectiveness of gender-neutral vaccination (GNV) versus female-only vaccination (FOV) with human papillomavirus (HPV) vaccination in Japan. METHODS: We modeled the public health impact and cost effectiveness of GNV versus FOV to prevent HPV-associated diseases in Japan over the next 100 years. We used one-way sensitivity analyses to examine the impact of varying key model input parameters and conducted scenario analyses to explore the effects of varying the vaccination coverage rate (VCR) of each cohort. RESULTS: In the base-case analysis, GNV averted additional cancer cases (17,228 female/6,033 male) and deaths (1,892 female/1,849 male) compared to FOV. When all HPV-associated diseases were considered, GNV had an incremental cost-effectiveness ratio of ¥4,732,320 (US$35,987)/quality-adjusted life year gained compared to FOV. The model was most sensitive to the discount rate and the disutility associated with HPV-related diseases. GNV had greater relative public health benefits when the female VCR was lower and was cost effective at a female VCR of 30%. CONCLUSIONS: Immediate implementation of GNV would reduce the disease burden and mortality associated with HPV in Japan, and would be cost effective compared to FOV if the female VCR remains low (30%).

Human papillomavirus (HPV) is a common sexually transmitted infection and, in Japan, the prevalence of HPV infection and the incidence of its associated diseases are high among both men and women. In the present manuscript we modeled the public health impact and cost effectiveness of gender-neutral vaccination versus female-only vaccination to prevent HPV-associated diseases in Japan over the next 100 years and found that immediate implementation of a gender-neutral vaccination strategy would reduce the burden and mortality associated with HPV in Japan.

COVID-19 host genetics and ABO blood group susceptibility.

Twenty-five susceptibility loci for SARS-CoV-2 infection and/or COVID-19 disease severity have been identified in the human genome by genome-wide association studies, and the most frequently replicated genetic findings for susceptibility are genetic variants at the ABO gene locus on chromosome 9q34.2, which is supported by the association between ABO blood group distribution and COVID-19. The ABO blood group effect appears to influence a variety of disease conditions and pathophysiological mechanisms associated with COVID-19. Transmission models for SARS-CoV-2 combined with observational public health and genome-wide data from patients and controls, as well as receptor binding experiments in cell lines and human samples, indicate that there may be a reduction or slowing of infection events by up to 60% in certain ABO blood group constellations of index and contact person in the early phase of a SARS-CoV-2 outbreak. The strength of the ABO blood group effect on reducing infection rates further depends on the distribution of the ABO blood groups in the respective population and the proportion of blood group O in that population. To understand in detail the effect of ABO blood groups on COVID-19, further studies are needed in relation to different demographic characteristics, but also in relation to recent data on reinfection with new viral variants and in the context of the human microbiome.

African swine fever detection and transmission estimates using homogeneous versus heterogeneous model formulation in stochastic simulations within pig premises.

Background: African swine fever (ASF) is one of the most important foreign animal diseases to the U.S. swine industry. Stakeholders in the swine production sector are on high alert as they witness the devastation of ongoing outbreaks in some of its most important trade partner countries. Efforts to improve preparedness for ASF outbreak management are proceeding in earnest and mathematical modeling is an integral part of these efforts. Aim: This study aimed to assess the impact on within-herd transmission dynamics of ASF when the models used to simulate transmission assume there is homogeneous mixing of animals within a barn. Methods: Barn-level heterogeneity was explicitly captured using a stochastic, individual pig-based, heterogeneous transmission model that considers three types of infection transmission, (1) within-pen via nose-to-nose contact; (2) between-pen via nose-to-nose contact with pigs in adjacent pens; and (3) both between- and within-pen via distance-independent mechanisms (e.g., via fomites). Predictions were compared between the heterogeneous and the homogeneous Gillespie models. Results: Results showed that the predicted mean number of infectious pigs at specific time points differed greatly between the homogeneous and heterogeneous models for scenarios with low levels of between-pen contacts via distance-independent pathways and the differences between the two model predictions were more pronounced for the slow contact rate scenario. The heterogeneous transmission model results also showed that it may take significantly longer to detect ASF, particularly in large barns when transmission predominantly occurs via nose-to-nose contact between pigs in adjacent pens. Conclusion: The findings emphasize the need for completing preliminary explorations when working with homogeneous mixing models to ascertain their suitability to predict disease outcomes.