A Comparison of Markov and Mechanistic Models for Soil-Transmitted Helminth Prevalence Projections in the Context of Survey Design

Globally, there are over 1 billion people infected with soil-transmitted helminths (STHs), mostly living in marginalized settings with inadequate sanitation in sub-Saharan Africa and Southeast Asia. The World Health Organization recommends an integrated approach to STH morbidity control through improved access to sanitation and hygiene education and the delivery of preventive chemotherapy (PC) to school-age children delivered through schools. Progress of STH control programs is currently estimated using a baseline (pre-PC) school-based prevalence survey and then monitored using periodical school-based prevalence surveys, known as Impact Assessment Surveys (IAS). We investigated whether integrating geostatistical methods with a Markov model or a mechanistic transmission model for projecting prevalence forward in time from baseline can improve IAS design strategies. To do this, we applied these 2 methods to prevalence data collected in Kenya, before evaluating and comparing their performance in accurately informing optimal survey design for a range of IAS sampling designs. We found that, although both approaches performed well, the mechanistic method more accurately projected prevalence over time and provided more accurate information for guiding survey design. Both methods performed less well in areas with persistent STH hotspots where prevalence did not decrease despite multiple rounds of PC. Our findings show that these methods can be useful tools for more efficient and accurate targeting of PC. The general framework built in this paper can also be used for projecting prevalence and informing survey design for other neglected tropical diseases.

Scenarios of future mpox outbreaks among men who have sex with men: a modelling study based on cross-sectional seroprevalence data from the Netherlands, 2022

BackgroundFollowing the 2022-2023 mpox outbreak, crucial knowledge gaps exist regarding orthopoxvirus-specific immunity in risk groups and its impact on future outbreaks.AimWe combined cross-sectional seroprevalence studies in two cities in the Netherlands with mathematical modelling to evaluate scenarios of future mpox outbreaks among men who have sex with men (MSM).MethodsSerum samples were obtained from 1,065 MSM attending Centres for Sexual Health (CSH) in Rotterdam or Amsterdam following the peak of the Dutch mpox outbreak and the introduction of vaccination. For MSM visiting the Rotterdam CSH, sera were linked to epidemiological and vaccination data. An in-house developed ELISA was used to detect vaccinia virus (VACV)-specific IgG. These observations were combined with published data on serial interval and vaccine effectiveness to inform a stochastic transmission model that estimates the risk of future mpox outbreaks.ResultsThe seroprevalence of VACV-specific antibodies was 45.4% and 47.1% in Rotterdam and Amsterdam, respectively. Transmission modelling showed that the impact of risk group vaccination on the original outbreak was likely small. However, assuming different scenarios, the number of mpox cases in a future outbreak would be markedly reduced because of vaccination. Simultaneously, the current level of immunity alone may not prevent future outbreaks. Maintaining a short time-to-diagnosis is a key component of any strategy to prevent new outbreaks.ConclusionOur findings indicate a reduced likelihood of large future mpox outbreaks among MSM in the Netherlands under current conditions, but emphasise the importance of maintaining population immunity, diagnostic capacities and disease awareness.

Estimating the Impact of Vaccination Campaigns on Measles Transmission in Somalia

Somalia is a complex and fragile setting with a demonstrated potential for disruptive, high-burden measles outbreaks. In response, since 2018, Somalian authorities have partnered with UNICEF and the WHO to implement measles vaccination campaigns across the country. In this paper, we create a Somalia-specific model of measles transmission based on a comprehensive epidemiological dataset including case-based surveillance, vaccine registries, and serological surveys. We use this model to assess the impact of these campaign interventions on Somalian's measles susceptibility, showing, for example, that across the roughly 10 million doses delivered, 1 of every 5 immunized a susceptible child. Finally, we use the model to explore a counter-factual epidemiology without the 2019-2020 campaigns, and we estimate that those interventions prevented over 10,000 deaths.

Male pathology regardless of behaviour drives transmission in an avian host-pathogen system

Host sex is an important source of heterogeneity in the severity of epidemics. Pinpointing the mechanisms causing this heterogeneity can be difficult because differences in behaviour among sexes (e.g. greater territorial aggression in males) can bias exposure risk, obfuscating the role of immune function, which can lead to differences in pathology, in driving differential susceptibility between sexes. Thus, sex-biased transmission driven by differences in immune function independent of behaviour is poorly understood, especially in non-mammalian systems. Here we examine the previously unexplored potential for male-biased pathology to affect transmission using an avian host-pathogen system. We employ a sex-dependent multistate transmission model parameterized with isolated, individual-based experimental exposures of domestic canaries and experimental transmission data of house finches. The experiment revealed that male birds have shorter incubation periods, longer recovery periods, higher pathogen burdens and greater disease pathology than females. Our model revealed that male-biased pathology led to epidemic size rapidly increasing with the proportion of male birds, with a nearly 10-fold increase in total epidemic size from an all-female to an all-male simulation. Our results demonstrate that female-biased resistance, independent of male behaviour, can drive sex-dependent transmission in wildlife, indicating that sex-based differences in immune function, not just differences in exposure risk, can shape epidemic dynamics.

A network suspected infectious disease model for the development of syphilis transmission from 2015 to 2021 in Hubei province, China

AIMS

Understanding the transmission mode of syphilis is essential to prevent and predict its future prevalence and to develop effective control measures. This study aimed to develop a network suspected infectious disease model to simulate the syphilis transmission.

METHODS AND RESULTS

The number of syphilis cases in Wuhan's Fourth Hospital, Hubei province, China, from October 2015 to July 2021 was collected. The simulation was carried out by interpersonal network-SI (suspected infectious) model based on temporal exponential family random graph models. Late latent syphilis and tertiary syphilis are predicted by December 2025. The validity of simulated value and real data was tested, including determination coefficient (R2), root means square error (RMSE), and means relative error (MRE). Moreover, we developed an online app that can more easily predict the number of syphilis infections in different scenarios by setting different parameters. Results showed that R2, RMSE, and MRE were 0.995, 36.19, and 6.31, respectively. Speed from latent infection to primary syphilis, primary syphilis to secondary syphilis, and susceptible group to latent infection decreased rapidly. The speed of transformation from secondary syphilis to early incubation period and early latent to late latent experienced a process from increase to decreased. Late latent to tertiary syphilis patients increased steadily. The number of late latent patients, early latent, invisible infection, primary syphilis, and secondary syphilis all increased at first and turn to decreased. However, tertiary syphilis continuously kept rising in the whole process. To better make use of the transmission model, an online application was developed (https://alanwu.shinyapps.io/MD-shiny/).

CONCLUSIONS

Based on the simulation that late latent and tertiary syphilis were steadily increasing, the prevention and treatment for syphilis were imperative.

Delineating the Seasonality of Varicella and Its Association With Climate in the Tropical Country of Colombia

BACKGROUND

Varicella causes a major health burden in many low- to middle-income countries located in tropical regions. Because of the lack of surveillance data, however, the epidemiology of varicella in these regions remains uncharacterized. In this study, based on an extensive dataset of weekly varicella incidence in children ≤10 during 2011-2014 in 25 municipalities, we aimed to delineate the seasonality of varicella across the diverse tropical climates of Colombia.

METHODS

We used generalized additive models to estimate varicella seasonality, and we used clustering and matrix correlation methods to assess its correlation with climate. Furthermore, we developed a mathematical model to examine whether including the effect of climate on varicella transmission could reproduce the observed spatiotemporal patterns.

RESULTS

Varicella seasonality was markedly bimodal, with latitudinal changes in the peaks' timing and amplitude. This spatial gradient strongly correlated with specific humidity (Mantel statistic = 0.412, P = .001) but not temperature (Mantel statistic = 0.077, P = .225). The mathematical model reproduced the observed patterns not only in Colombia but also México, and it predicted a latitudinal gradient in Central America.

CONCLUSIONS

These results demonstrate large variability in varicella seasonality across Colombia and suggest that spatiotemporal humidity fluctuations can explain the calendar of varicella epidemics in Colombia, México, and potentially in Central America.

Testing Whether Higher Contact Among the Vaccinated Can Be a Mechanism for Observed Negative Vaccine Effectiveness

Evidence from early observational studies suggested negative vaccine effectiveness (${V}_{Eff}$) for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant. Since true ${V}_{Eff}$ is unlikely to be negative, we explored how differences in contact among vaccinated persons (e.g., potentially from the implementation of vaccine mandates) could lead to observed negative ${V}_{Eff}$. Using a susceptible-exposed-infectious-recovered (SEIR) transmission model, we examined how vaccinated-contact heterogeneity, defined as an increase in the contact rate only between vaccinated individuals, interacted with 2 mechanisms of vaccine efficacy: vaccine efficacy against susceptibility ($V{E}_S$) and vaccine efficacy against infectiousness ($V{E}_I$), to produce underestimated and in some cases, negative measurements of ${V}_{Eff}$. We found that vaccinated-contact heterogeneity led to negative estimates when $V{E}_I$, and especially $V{E}_S$, were low. Moreover, we determined that when contact heterogeneity was very high, ${V}_{Eff}$ could still be underestimated given relatively high vaccine efficacies (0.7), although its effect on ${V}_{Eff}$ was strongly reduced. We also found that this contact heterogeneity mechanism generated a signature temporal pattern: The largest underestimates and negative measurements of ${V}_{Eff}$ occurred during epidemic growth. Overall, our research illustrates how vaccinated-contact heterogeneity could have feasibly produced negative measurements during the Omicron period and highlights its general ability to bias observational studies of ${V}_{Eff}$.

Modelling the control of bovine brucellosis in India

Brucellosis imposes substantial impacts on livestock production and public health worldwide. A stochastic, age-structured model incorporating herd demographics was developed describing within- and between-herd transmission of Brucella abortus in dairy cattle herds. The model was fitted to data from a cross-sectional study conducted in Punjab State of India and used to evaluate the effectiveness of control strategies under consideration. Based on model results, stakeholder acceptance and constraints regarding vaccine supply, vaccination of replacement calves in large farms should be prioritized. Test and removal applied at early stages of the control programme where seroprevalence is high would not constitute an effective or acceptable use of resources because significant numbers of animals would be 'removed' (culled or not used for breeding) based on false positive results. To achieve sustained reductions in brucellosis, policymakers must commit to maintaining vaccination in the long term, which may eventually reduce frequency of infection in the livestock reservoir to a low enough level for elimination to be a realistic objective. This work provides key strategic insights into the control of brucellosis in India, which has the largest cattle population globally, and a general modelling framework for evaluating control strategies in endemic settings.

Transmission trends of the global COVID-19 pandemic with combined effects of adaptive behaviours and vaccination

We developed a mechanism model which allows for simulating the novel coronavirus (COVID-19) transmission dynamics with the combined effects of human adaptive behaviours and vaccination, aiming at predicting the end time of COVID-19 infection in global scale. Based on the surveillance information (reported cases and vaccination data) between 22 January 2020 and 18 July 2022, we validated the model by Markov Chain Monte Carlo (MCMC) fitting method. We found that (1) if without adaptive behaviours, the epidemic could sweep the world in 2022 and 2023, causing 3.098 billion of human infections, which is 5.39 times of current number; (2) 645 million people could be avoided from infection due to vaccination; and (3) in current scenarios of protective behaviours and vaccination, infection cases would increase slowly, levelling off around 2023, and it would end completely in June 2025, causing 1.024 billion infections, with 12.5 million death. Our findings suggest that vaccination and the collective protection behaviour remain the key determinants against the global process of COVID-19 transmission.

Corrigendum: A practical introduction to mechanistic modeling of disease transmission in veterinary science

[This corrects the article DOI: 10.3389/fvets.2020.546651.].

Optimizing response to an introduction of African swine fever in wild pigs

African swine fever virus (ASFv) is a virulent pathogen that threatens domestic swine industries globally and persists in wild boar populations in some countries. Persistence in wild boar can challenge elimination and prevent disease-free status, making it necessary to address wild swine in proactive response plans. In the U.S., invasive wild pigs are abundant and found across a wide range of ecological conditions that could drive different epidemiological dynamics among populations. Information on size of control areas required to rapidly eliminate ASFv in wild pigs and how this area should change with management constraints and local ecology are needed to optimize response planning. We developed a spatially-explicit disease transmission model contrasting wild pig movement and contact ecology in two ecosystems in southeastern U.S. We simulated ASFv spread and determined optimal response area (reported as radius of a circle) for eliminating ASFv rapidly over a range of detection times (when ASFv is detected relative to true date of introduction), culling capacities (proportion of wild pigs in the culling zone removed weekly), and wild pig densities. Large radii for response areas (14 km) were needed under most conditions but could be shortened with early detection (≤ 8 weeks) and high culling capacities (≥ 15% weekly). Under most conditions ASFv was eliminated in less than 22 weeks using optimal control radii, although ecological conditions with high rates of wild pig movement required higher culling capacities (≥ 10% weekly) for elimination within one year. Results highlight the importance of adjusting response plans based on local ecology and show wild pig movement is a better predictor of optimal response area than numbers of ASFv cases early in the outbreak trajectory. Our framework provides a tool for determining optimal control plans in different areas, guiding expectations of response impacts, and planning resources needed for rapid elimination. This article is protected by copyright. All rights reserved.

Modeling the effect of Fangcang shelter hospitals on the control of COVID-19 epidemic

The ongoing COVID-19 pandemic has posed a tremendous threat to the public and health authorities. Wuhan, as one of the cities experiencing the earliest COVID-19 outbreak, has successfully tackled the epidemic finally. The main reason is the implementing of Fangcang shelter hospitals, which rapidly and massively scale the health system's capacity to treat COVID-19 confirmed cases with mild symptoms. To give insights on what degree Fangcang shelter hospitals have contained COVID-19 in Wuhan, we proposed a piecewise smooth model regarding the patient triage scheme and the bed capacities of Fangcang shelter hospitals and designated hospitals. We used data on the cumulative number of confirmed cases, recovered cases, deaths, and data on the number of hospitalized individuals in Fangcang shelter hospitals and designated hospitals in Wuhan to parameterize the targeted model. Our results showed that diminishing the bed capacity or delaying the opening time of Fangcang shelter hospitals, both would result in worsening the epidemic by increasing the total number of infectives and hospitalized individuals and the effective reproduction numberR e ( t ) . The findings demonstrated that Fangcang shelter hospitals avoided 17,013 critical infections and 17,823 total infections while it saved 7 days during the process of controlling the effective reproduction numberR e ( t ) < 1 . Our study highlighted the critical role of Fangcang shelter hospitals in curbing and eventually stopping COVID-19 outbreak in Wuhan, China. These findings may provide a valuable reference for decision-makers in regarding ramping up the health system capacity to isolate groups of people with mild symptoms in areas of widespread infection.

Epidemiological Characteristics and Transmissibility of Human Immunodeficiency Virus in Nanning City, China, 2001-2020

Background: Human immunodeficiency virus (HIV) is a single-stranded RNA virus that can weaken the body's cellular and humoral immunity and is a serious disease without specific drug management and vaccine. This study aimed to evaluate the epidemiologic characteristics and transmissibility of HIV.

Methods: Data on HIV follow-up were collected in Nanning City, Guangxi Zhuang Autonomous, China. An HIV transmission dynamics model was built to simulate the transmission of HIV and estimate its transmissibility by comparing the effective reproduction number (R_eff) at different stages: the rapid growth period from January 2001 to March 2005, slow growth period from April 2005 to April 2011, and the plateau from May 2011 to December 2019 of HIV in Nanning City.

Results: High-risk areas of HIV prevalence in Nanning City were mainly concentrated in suburbs. Furthermore, high-risk groups were those of older age, with lower income, and lower education levels. The R_eff in each stage (rapid growth, slow growth, and plateau) were 2.74, 1.62, and 1.15, respectively, which suggests the transmissibility of HIV in Nanning City has declined and prevention and control measures have achieved significant results.

Conclusion: Over the past 20 years, the HIV incidence in Nanning has remained at a relatively high level, but its development trend has been curbed. Transmissibility was reduced from 2.74 to 1.15. Therefore, the prevention and treatment measures in Nanning City have achieved significant improvement.

Role of Asymptomatic COVID-19 Cases in Viral Transmission: Findings From a Hierarchical Community Contact Network Model

As part of ongoing efforts to contain the coronavirus disease (COVID-19) pandemic, understanding the role of asymptomatic patients in the transmission system is essential for infection control. However, the optimal approach to risk assessment and management of asymptomatic cases remains unclear. This study proposed a Susceptible, Exposed, Infectious, No symptoms, Hospitalized and reported, Recovered, Death (SEINRHD) epidemic propagation model. The model was constructed based on epidemiological characteristics of COVID-19 in China and accounting for the heterogeneity of social contact networks. The early community outbreaks in Wuhan were reconstructed and fitted with the actual data. We used this model to assess epidemic control measures for asymptomatic cases in three dimensions. The impact of asymptomatic cases on epidemic propagation was examined based on the effective reproduction number, abnormally high transmission events, and type and structure of transmission. Management of asymptomatic cases can help flatten the infection curve. Tracing 75% of the asymptomatic cases corresponds to a 32.5% overall reduction in new cases (compared with tracing no asymptomatic cases). Regardless of population-wide measures, household transmission is higher than other types of transmission, accounting for an estimated 50% of all cases. The magnitude of tracing of asymptomatic cases is more important than the timing; when all symptomatic patients were traced, tested, and isolated in a timely manner, the overall epidemic was not sensitive to the time of implementing the measures to trace asymptomatic patients. Disease control and prevention within families should be emphasized during an epidemic. Note to Practitioners-This article addresses the urgent need to assess the risk of another COVID-19 outbreak caused by asymptomatic cases and to find the optimal, most practical approach to asymptomatic case management. Previous studies mostly focused on the clinical and statistical characteristics of asymptomatic cases; few have evaluated the impact of asymptomatic case measures using mathematical modeling at the community scale. This study proposed a Susceptible, Exposed, Infectious, No symptoms, Hospitalized and reported, Recovered, Death (SEINRHD) propagation model based on local community structures and social contact networks, according to the development characteristics and trend of COVID-19 in a Chinese community. The conclusion provides theoretical support for emergency work of relevant departments in different periods of an epidemic. In the early stages of the epidemic, timely detection and isolation of symptomatic patients should be a priority. Where there are surplus resources for epidemic prevention, the authorities should consider increasing the proportion of asymptomatic patients being traced. Epidemic prevention measures among family members should be a primary focus of attention. This combination of strategies can help reduce the rate of viral transmission and result in extinguishing the epidemic.

Date of introduction and epidemiologic patterns of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Mogadishu, Somalia: estimates from transmission modelling of satellite-based excess mortality data in 2020

Background: In countries with weak surveillance systems, confirmed coronavirus disease 2019 (COVID-19) deaths are likely to underestimate the pandemic's death toll. Many countries also have incomplete vital registration systems, hampering excess mortality estimation. Here, we fitted a dynamic transmission model to satellite imagery data of cemeteries in Mogadishu, Somalia during 2020 to estimate the date of introduction and other epidemiologic parameters of the early spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in this low-income, crisis-affected setting. Methods: We performed Markov chain Monte Carlo (MCMC) fitting with an age-structured compartmental COVID-19 model to provide median estimates and credible intervals for the date of introduction, the basic reproduction number ( R 0 ) and the effect of non-pharmaceutical interventions (NPIs) up to August 2020. Results: Under the assumption that excess deaths in Mogadishu March-August 2020 were attributable to SARS-CoV-2 infections, we arrived at median estimates of November-December 2019 for the date of introduction and low R 0 estimates (1.4-1.7) reflecting the slow and early rise and long plateau of excess deaths. The date of introduction, the amount of external seeding, the infection fatality rate (IFR) and the effectiveness of NPIs are correlated parameters and not separately identifiable in a narrow range from deaths data. Nevertheless, to obtain introduction dates no earlier than November 2019 a higher population-wide IFR (≥0.7%) had to be assumed than obtained by applying age-specific IFRs from high-income countries to Somalia's age structure. Conclusions: Model fitting of excess mortality data across a range of plausible values of the IFR and the amount of external seeding suggests an early SARS-CoV-2 introduction event may have occurred in Somalia in November-December 2019. Transmissibility in the first epidemic wave was estimated to be lower than in European settings. Alternatively, there was another, unidentified source of sustained excess mortality in Mogadishu from March to August 2020.

School and community reopening during the COVID-19 pandemic: a mathematical modelling study

Operating schools safely during the COVID-19 pandemic requires a balance between health risks and the need for in-person learning. Using demographic and epidemiological data between 31 July and 23 November 2020 from Toronto, Canada, we developed a compartmental transmission model with age, household and setting structure to study the impact of schools reopening in September 2020. The model simulates transmission in the home, community and schools, accounting for differences in infectiousness between adults and children, and accounting for work-from-home and virtual learning. While we found a slight increase in infections among adults (2.2%) and children (4.5%) within the first eight weeks of school reopening, transmission in schools was not the key driver of the virus resurgence in autumn 2020. Rather, it was community spread that determined the outbreak trajectory, primarily due to increases in contact rates among adults in the community after school reopening. Analyses of cross-infection among households, communities and schools revealed that home transmission is crucial for epidemic progression and safely operating schools, while the degree of in-person attendance has a larger impact than other control measures in schools. This study suggests that safe school reopening requires the strict maintenance of public health measures in the community.

High Infection Secondary Attack Rates of Severe Acute Respiratory Syndrome Coronavirus 2 in Dutch Households Revealed by Dense Sampling

BACKGROUND

Indoor environments are considered one of the main settings for transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Households in particular represent a close-contact environment with high probability of transmission between persons of different ages and roles in society.

METHODS

Households with a laboratory-confirmed SARS-CoV-2 positive case in the Netherlands (March-May 2020) were included. At least 3 home visits were performed during 4-6 weeks of follow-up, collecting naso- and oropharyngeal swabs, oral fluid, feces and blood samples from all household members for molecular and serological analyses. Symptoms were recorded from 2 weeks before the first visit through to the final visit. Infection secondary attack rates (SAR) were estimated with logistic regression. A transmission model was used to assess household transmission routes.

RESULTS

A total of 55 households with 187 household contacts were included. In 17 households no transmission took place; in 11 households all persons were infected. Estimated infection SARs were high, ranging from 35% (95% confidence interval [CI], 24%-46%) in children to 51% (95% CI, 39%-63%) in adults. Estimated transmission rates in the household were high, with reduced susceptibility of children compared with adolescents and adults (0.67; 95% CI, .40-1.1).

CONCLUSION

Estimated infection SARs were higher than reported in earlier household studies, presumably owing to our dense sampling protocol. Children were shown to be less susceptible than adults, but the estimated infection SAR in children was still high. Our results reinforce the role of households as one of the main multipliers of SARS-CoV-2 infection in the population.

Model-based assessment of SARS-CoV-2 Delta variant transmission dynamics within partially vaccinated K-12 school populations

BACKGROUND

We examined school reopening policies amidst ongoing transmission of the highly transmissible Delta variant, accounting for vaccination among individuals ≥12 years.

METHODS

We collected data on social contacts among school-aged children in the California Bay Area and developed an individual-based transmission model to simulate transmission of the Delta variant of SARS-CoV-2 in schools. We evaluated the additional infections in students and teachers/staff resulting over a 128-day semester from in-school instruction compared to remote instruction when various NPIs (mask use, cohorts, and weekly testing of students/teachers) were implemented, across various community-wide vaccination coverages (50%, 60%, 70%), and student (≥12 years) and teacher/staff vaccination coverages (50% - 95%).

FINDINGS

At 70% vaccination coverage, universal masking reduced infections by >57% among students. Masking plus 70% vaccination coverage enabled achievement of <50 excess cases per 1,000 students/teachers, but stricter risk tolerances, such as <25 excess infections per 1,000 students/teachers, required a cohort approach in elementary and middle school populations. In the absence of NPIs, increasing the vaccination coverage of community members from 50% to 70% or elementary teachers from 70% to 95% reduced the excess rate of infection among elementary school students attributable to school transmission by 24% and 37%, respectively.

INTERPRETATIONS

Amidst Delta variant circulation, we found that schools are not inherently low risk, yet can be made so with high community vaccination coverages and masking. Vaccination of adults protects unvaccinated children.

FUNDING

National Science Foundation grant no. 2032210; National Institutes of Health grant nos. R01AI125842 and R01AI148336; MIDAS Coordination Center (MIDASSUP2020-4).

COVID-19 Transmission at Schools in Japan

The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), remains a global public health concern in 2021. However, the risk of attending schools during the pandemic remains unevaluated. This study estimated the secondary transmission rate at schools using the results of a real-time reverse transcription-polymerase chain reaction (RT-PCR) screening test performed between July 2020 and April 2021, before starting the nationwide mass vaccination. A total of 1,924 students (20 RT-PCR-positive; 1.0%) from 52 schools or preschools were evaluated, together with 1,379 non-adults (95 RT-PCR-positive; 6.9%) exposed to SARS-CoV-2 in non-school environments. Assuming that the infectious index cases were asymptomatic and the transmission at schools followed a Bernoulli process, we estimated the probability of transmission after each contact at school as approximately 0.005 (0.5% per contact) with the current infection prevention measures at schools in Japan (i.e., hand hygiene, physical distancing, wearing masks, and effective ventilation). Furthermore, assuming that all children are capable of carrying the infection, then contact between an index case and 20-30 students per day at schools would yield the expected value for secondary cases of ≥ 1.0, during the 10 days of the infectious period. In conclusion, with the current infection prevention measures at schools in Japan, secondary transmission at schools would occur in approximately every 200 contacts. When considering this rate, compliance with the current infection prevention measures at schools and early detection and quarantine of the index cases would be effective in preventing the spread of COVID-19 at schools.

Compartment Niche Shapes the Assembly and Network of Cannabis sativa-Associated Microbiome

Interactions between plants and microbes may promote the growth of plants and regulate the production of secondary metabolites. Hemp (Cannabis sativa) is an annual herb and an important commercial crop. However, the assembly and network of hemp-associated microbiomes inhabiting in soil and plant compartments have not been comprehensively understood. This work investigated the assembly and network of bacterial and fungal communities living in soils (bulk and rhizosphere) and plant compartments (root, stem, leaf, and flower) of four hemp ecotypes cultivated in the same habitat. Microbiome assembly was predominantly shaped by compartment niche. Microbial alpha diversity was the highest in soil, continually decreased from root to flower. Core bacterial genera Pseudomonas, Bacillus, Rhizobium, Planococcus, and Sphingomonas were mostly enriched in aerial endosphere niches; Clitopilus, Plectosphaerella, and Mortierella were enriched in belowground endosphere. Microbial network complexity and connectivity decreased from root to flower. According to source tracking analysis, hemp microbiota primarily originated from soil and were subsequently filtered in different plant compartments. This work provides details on hemp-associated microbiome along the soil-plant continuum and a comprehensive understanding of the origin and transmission mode of endophytes in hemp.

Date of introduction and epidemiologic patterns of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Mogadishu, Somalia: estimates from transmission modelling of satellite-based excess mortality data in 2020

Background: In countries with weak surveillance systems, confirmed coronavirus disease 2019 (COVID-19) deaths are likely to underestimate the pandemic's death toll. Many countries also have incomplete vital registration systems, hampering excess mortality estimation. Here, we fitted a dynamic transmission model to satellite imagery data of cemeteries in Mogadishu, Somalia during 2020 to estimate the date of introduction and other epidemiologic parameters of the early spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in this low-income, crisis-affected setting. Methods: We performed Markov chain Monte Carlo (MCMC) fitting with an age-structured compartmental COVID-19 model to provide median estimates and credible intervals for the date of introduction, the basic reproduction number ( R 0 ) and the effect of non-pharmaceutical interventions (NPIs) up to August 2020. Results: Under the assumption that excess deaths in Mogadishu March-August 2020 were attributable to SARS-CoV-2 infections, we arrived at median estimates of November-December 2019 for the date of introduction and low R 0 estimates (1.4-1.7) reflecting the slow and early rise and long plateau of excess deaths. The date of introduction, the amount of external seeding, the infection fatality rate (IFR) and the effectiveness of NPIs are correlated parameters and not separately identifiable in a narrow range from deaths data. Nevertheless, to obtain introduction dates no earlier than November 2019 a higher population-wide IFR (≥0.7%) had to be assumed than obtained by applying age-specific IFRs from high-income countries to Somalia's age structure. Conclusions: Model fitting of excess mortality data across a range of plausible values of the IFR and the amount of external seeding suggests an early SARS-CoV-2 introduction event may have occurred in Somalia in November-December 2019. Transmissibility in the first epidemic wave was estimated to be lower than in European settings. Alternatively, there was another, unidentified source of sustained excess mortality in Mogadishu from March to August 2020.

The Statewide Economic Impact of Child Care-Associated Viral Acute Gastroenteritis Infections

INTRODUCTION

More than 65% of children aged ≤5 years in the United States require out-of-home child care. Child care attendance has been associated with an elevated risk of respiratory illness and acute gastroenteritis (AGE). While child care-associated respiratory disease cases are more numerous, AGE is associated with more severe symptoms and more than double the number of absences from child care. In addition, viral pathogens such as norovirus, rotavirus, and adenovirus are highly infectious and may be spread to parents and other household members. As a result, child care-associated viral AGE may incur substantial economic costs due to healthcare service usage and lost productivity.

METHODS

We used surveillance data from a network of child care centers in Washtenaw County, Michigan, as well as a household transmission model to estimate the annual cost of child care-associated viral AGE in the state of Michigan.

RESULTS

We estimated that child care-associated viral AGE in Michigan costs between $15 million and $31 million annually, primarily due to lost productivity.

CONCLUSIONS

The economic burden of child care-associated infections is considerable. Effective targeted interventions are needed to mitigate this impact.

A Framework for Weather-Driven Dengue Virus Transmission Dynamics in Different Brazilian Regions

This study investigated a model to assess the role of climate fluctuations on dengue (DENV) dynamics from 2010 to 2019 in four Brazilian municipalities. The proposed transmission model was based on a preexisting SEI-SIR model, but also incorporates the vector vertical transmission and the vector's egg compartment, thus allowing rainfall to be introduced to modulate egg-hatching. Temperature and rainfall satellite data throughout the decade were used as climatic model inputs. A sensitivity analysis was performed to understand the role of each parameter. The model-simulated scenario was compared to the observed dengue incidence and the findings indicate that the model was able to capture the observed seasonal dengue incidence pattern with good accuracy until 2016, although higher deviations were observed from 2016 to 2019. The results further demonstrate that vertical transmission fluctuations can affect attack transmission rates and patterns, suggesting the need to investigate the contribution of vertical transmission to dengue transmission dynamics in future assessments. The improved understanding of the relationship between different environment variables and dengue transmission achieved by the proposed model can contribute to public health policies regarding mosquito-borne diseases.

VIVID: In Vivo End-to-End Molecular Communication Model for COVID-19

As an alternative to ongoing efforts for vaccine development, scientists are exploring novel approaches to provide innovative therapeutics, such as nanoparticle- and stem cell-based treatments. Thus, understanding the transmission and propagation dynamics of coronavirus inside the respiratory system has attracted researchers' attention. In this work, we model the transmission and propagation of coronavirus inside the respiratory tract, starting from the nasal area to alveoli using molecular communication theory. We performed experiments using COMSOL, a finite-element multiphysics simulation software, and Python-based simulations to analyze the end-to-end communication model in terms of path loss, delay, and gain. The analytical results show the correlation between the channel characteristics and pathophysiological properties of coronavirus. For the initial 50% of the maximum production rate of virus particles, the path loss increases more than 16 times than the remaining 50%. The delayed response of the immune system and increase in the absorption of virus particles inside the respiratory tract delay the arrival of virus particles at the alveoli. Furthermore, the results reveal that the virus load is more in case of asthmatic patients as compared to the normal subjects.

Model-based assessment of SARS-CoV-2 Delta variant transmission dynamics within partially vaccinated K-12 school populations

BACKGROUND

We examined school reopening policies amidst rising transmission of the highly transmissible Delta variant, accounting for vaccination among individuals aged 12 years and older, with the goal of characterizing risk to students and teachers under various within-school non-pharmaceutical interventions (NPIs) combined with specific vaccination coverage levels.

METHODS

We developed an individual-based transmission model to simulate transmission of the Delta variant of SARS-CoV-2 among a synthetic population, representative of Bay Area cities. We parameterized the model using community contact rates from vaccinated households ascertained from a household survey of Bay Area families with children conducted between February - April, 2021.

INTERVENTIONS AND OUTCOMES

We evaluated the additional infections in students and teachers/staff resulting over a 128-day semester from in-school instruction compared to remote instruction when various NPIs (mask use, cohorts, and weekly testing of students/teachers) were implemented in schools, across various community-wide vaccination coverages (50%, 60%, 70%), and student (≥12 years) and teacher/staff vaccination coverages (50% - 95%). We quantified the added benefit of universal masking over masking among unvaccinated students and teachers, across varying levels of vaccine effectiveness (45%, 65%, 85%), and compared results between Delta and Alpha variant circulation.

RESULTS

The Delta variant sharply increases the risk of within-school COVID-transmission when compared to the Alpha variant. In our highest risk scenario (50% community and within-school vaccine coverage, no within-school NPIs, and predominant circulation of the Delta variant), we estimated that an elementary school could see 33-65 additional symptomatic cases of COVID-19 over a four-month semester (depending on the relative susceptibility of children <10 years). In contrast, under the Bay Area reopening plan (universal mask use, community and school vaccination coverage of 70%), we estimated excess symptomatic infection attributable to school reopening among 2.0-9.7% of elementary students (8-36 excess symptomatic cases per school over the semester), 3.0% of middle school students (13 cases per school) and 0.4% of high school students (3 cases per school). Excess rates among teachers attributable to reopening were similar. Achievement of lower risk tolerances, such as <5 excess infections per 1,000 students or teachers, required a cohort approach in elementary and middle school populations. In the absence of NPIs, increasing the vaccination coverage of community members from 50% to 70% or elementary teachers from 70% to 95% reduced the estimated excess rate of infection among elementary school students attributable to school transmission by 24% and 41%, respectively. We estimated that with 70% coverage of the eligible community and school population with a vaccine that is ≤65% effective, universal masking can avert more cases than masking of unvaccinated persons alone.

CONCLUSIONS

Amidst circulation of the Delta variant, our findings demonstrated that schools are not inherently low risk, yet can be made so with high community vaccination coverages and universal masking. Vaccination of adult community members and teachers protects unvaccinated elementary and middle school children. Elementary and middle schools that can support additional interventions, such as cohorts and testing, should consider doing so, particularly if additional studies find that younger children are equally as susceptible as adults to the Delta variant of SARS-CoV-2.

LIMITATIONS

We did not consider the effect of social distancing in classrooms, or variation in testing frequency, and considerable uncertainty remains in key transmission parameters.

Novel coronavirus 2019-nCoV (COVID-19): early estimation of epidemiological parameters and epidemic size estimates

Since it was first identified, the epidemic scale of the recently emerged novel coronavirus (2019-nCoV) in Wuhan, China, has increased rapidly, with cases arising across China and other countries and regions. Using a transmission model, we estimate a basic reproductive number of 3.11 (95% CI, 2.39-4.13), indicating that 58-76% of transmissions must be prevented to stop increasing. We also estimate a case ascertainment rate in Wuhan of 5.0% (95% CI, 3.6-7.4). The true size of the epidemic may be significantly greater than the published case counts suggest, with our model estimating 21 022 (prediction interval, 11 090-33 490) total infections in Wuhan between 1 and 22 January. We discuss our findings in the light of more recent information. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'.

Novel coronavirus 2019-nCoV (COVID-19): early estimation of epidemiological parameters and epidemic size estimates

Since it was first identified, the epidemic scale of the recently emerged novel coronavirus (2019-nCoV) in Wuhan, China, has increased rapidly, with cases arising across China and other countries and regions. Using a transmission model, we estimate a basic reproductive number of 3.11 (95% CI, 2.39-4.13), indicating that 58-76% of transmissions must be prevented to stop increasing. We also estimate a case ascertainment rate in Wuhan of 5.0% (95% CI, 3.6-7.4). The true size of the epidemic may be significantly greater than the published case counts suggest, with our model estimating 21 022 (prediction interval, 11 090-33 490) total infections in Wuhan between 1 and 22 January. We discuss our findings in the light of more recent information. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'.

Cost-Effectiveness of Pertussis Vaccination Schedule in Israel

Pertussis is a highly contagious bacterial disease that primarily affects infants. To optimize the pertussis vaccination schedule in Israel and evaluate the cost-effectiveness of alternative strategies that add or remove booster doses, we developed an age-structured model for pertussis transmission. Our model was calibrated using 16 years of data from laboratory-confirmed pertussis cases in Israel. Costs and quality-adjusted life years (QALYs) projected by the model within 12 years from the implementation of the considered interventions were compared with the current vaccination schedule. We found that by using the same number of vaccines administered today, the targeting of children at the age of six instead of seven would be predicted to be the optimal schedule to decrease both outpatient visits and hospitalizations. We also found that any increase in maternal vaccination coverage is likely to be cost-effective, with an incremental cost-effectiveness ratio of $77,000–$97,000 per QALY. By contrast, the contribution of the second booster dose is limited, with a probability of only 0.6 to be cost-effective at $110,000/QALY saved. Additional effort should be invested to encourage maternal vaccination against pertussis. We recommend moving the first booster to age six and prudently considering the necessity of the second booster dose.

Design and implementation of a hand-held robot-assisted minimally invasive surgical device with enhanced intuitive manipulability and stable grip force

BACKGROUND

The conventional hand-held minimally invasive surgical devices commonly suffer from non-intuitive manipulability and restricted flexibility for operation.

METHODS

A hand-held surgical device with enhanced intuitive manipulability and stable grip force was proposed for minimally invasive surgery (MIS). The dexterous instrument and isomorphic handle were designed, and the cable transmission structure and model of the instrument were analysed. A modelling method for grip force pre-compensation was proposed to produce stable grip forces under different posture.

RESULTS

The prototype of the proposed MIS device was developed, and the related experiments were carried out. The maximum opening angle error was 1.2°. Compared with the non-compensation model, the variation of grip force reduced 8 times with the pre-compensation model. The animal vivo experiments verified the feasibility and practicability of the device.

CONCLUSIONS

The proposed hand-held device could provide intuitive manipulability and stable operation, which contributes to the performance improvement of the MIS.

Optimizing the early detection of low pathogenic avian influenza H7N9 virus in live bird markets

In Southeast Asia, surveillance at live bird markets (LBMs) has been identified as crucial for detecting avian influenza viruses (AIV) and reducing the risk of human infections. However, the design of effective surveillance systems in LBMs remains complex given the rapid turn-over of poultry. We developed a deterministic transmission model to provide guidance for optimizing AIV surveillance efforts. The model was calibrated to fit one of the largest LBMs in northern Vietnam at high risk of low pathogenic H7N9 virus introduction from China to identify the surveillance strategy that optimizes H7N9 detection. Results show that (i) using a portable diagnostic device would slightly reduce the number of infected birds leaving the LBM before the first detection, as compared to a laboratory-based diagnostic strategy, (ii) H7N9 detection could become more timely by sampling birds staying overnight, just before new susceptible birds are introduced at the beginning of a working day, and (iii) banning birds staying overnight would represent an effective intervention to reduce the risk of H7N9 spread but would decrease the likelihood of virus detection if introduced. These strategies should receive high priority in Vietnam and other Asian countries at risk of H7N9 introduction.

School closures reduced social mixing of children during COVID-19 with implications for transmission risk and school reopening policies

School closures may reduce the size of social networks among children, potentially limiting infectious disease transmission. To estimate the impact of K-12 closures and reopening policies on children's social interactions and COVID-19 incidence in California's Bay Area, we collected data on children's social contacts and assessed implications for transmission using an individual-based model. Elementary and Hispanic children had more contacts during closures than high school and non-Hispanic children, respectively. We estimated that spring 2020 closures of elementary schools averted 2167 cases in the Bay Area (95% CI: -985, 5572), fewer than middle (5884; 95% CI: 1478, 11.550), high school (8650; 95% CI: 3054, 15 940) and workplace (15 813; 95% CI: 9963, 22 617) closures. Under assumptions of moderate community transmission, we estimated that reopening for a four-month semester without any precautions will increase symptomatic illness among high school teachers (an additional 40.7% expected to experience symptomatic infection, 95% CI: 1.9, 61.1), middle school teachers (37.2%, 95% CI: 4.6, 58.1) and elementary school teachers (4.1%, 95% CI: -1.7, 12.0). However, we found that reopening policies for elementary schools that combine universal masking with classroom cohorts could result in few within-school transmissions, while high schools may require masking plus a staggered hybrid schedule. Stronger community interventions (e.g. remote work, social distancing) decreased the risk of within-school transmission across all measures studied, with the influence of community transmission minimized as the effectiveness of the within-school measures increased.

Modelling the effect of market forces on the impact of introducing human immunodeficiency virus pre-exposure prophylaxis among female sex workers

Pre-exposure prophylaxis (PrEP) to prevent human immunodeficiency virus (HIV) enables female sex workers (FSWs) to protect themselves from HIV without relying on clients using condoms. Yet, because PrEP reduces HIV risk, financial incentives to not use condoms may lead to risk compensation: reductions in condom use and/or increases in commercial sex, and may reduce the price of unprotected sex. In this analysis, we integrate market forces into a dynamic HIV transmission model to assess how risk compensation could change the impact of PrEP among FSWs and clients. We parameterise how sexual behavior may change with PrEP use among FSWs using stated preference data combined with economic theory. Our projections suggest the impact of PrEP is sensitive to risk compensatory behaviors driven by changes in the economics of sex work. Condom substitution could reduce the impact of PrEP on HIV incidence by 55%, while increases in the frequency of commercial sex to counter decreases in the price charged for unprotected sex among PrEP users could entirely mitigate the impact of PrEP. Accounting for competition between PrEP users and nonusers exacerbates this further. Alternative scenarios where increases in unprotected sex among PrEP users are balanced by decreases in non-PrEP users have the opposite effect, resulting in PrEP having much greater impact. Intervention studies need to determine how HIV prevention products may change the economics of sex work and provision of unprotected sex to enable a better understanding of their impact.

A Practical Introduction to Mechanistic Modeling of Disease Transmission in Veterinary Science

Computer-based disease spread models are frequently used in veterinary science to simulate disease spread. They are used to predict the impacts of the disease, plan and assess surveillance, or control strategies, and provide insights about disease causation by comparing model outputs with real life data. There are many types of disease spread models, and here we present and describe the implementation of a particular type: individual-based models. Our aim is to provide a practical introduction to building individual-based disease spread models. We also introduce code examples with the goal to make these techniques more accessible to those who are new to the field. We describe the important steps in building such models before, during and after the programming stage, including model verification (to ensure that the model does what was intended), validation (to investigate whether the model results reflect the modeled system), and convergence analysis (to ensure models of endemic diseases are stable before outputs are collected). We also describe how sensitivity analysis can be used to assess the potential impact of uncertainty about model parameters. Finally, we provide an overview of some interesting recent developments in the field of disease spread models.

Understanding the Importance of Contact Heterogeneity and Variable Infectiousness in the Dynamics of a Large Norovirus Outbreak

BACKGROUND

Large norovirus (NoV) outbreaks are explosive in nature and vary widely in final size and duration, suggesting that superspreading combined with heterogeneous contact may explain these dynamics. Modeling tools that can capture heterogeneity in infectiousness and contact are important for NoV outbreak prevention and control, yet they remain limited.

METHODS

Data from a large NoV outbreak at a Dutch scout jamboree, which resulted in illness among 326 (of 4500 total) individuals from 7 separate camps, were used to examine the contributions of individual variation in infectiousness and clustered contact patterns to the transmission dynamics. A Bayesian hierarchical model of heterogeneous, clustered outbreak transmission was applied to represent (1) between-individual heterogeneity in infectiousness and (2) heterogeneous patterns of contact.

RESULTS

We found wide heterogeneity in infectiousness across individuals, suggestive of superspreading. Nearly 50% of individual infectiousness was concentrated in the individual's subcamp of residence, with the remainder distributed over other subcamps. This suggests a source-and-sink dynamic in which subcamps with greater average infectiousness fed cases to those with a lower transmission rate. Although the per capita transmission rate within camps was significantly greater than that between camps, the large pool of susceptible individuals across camps enabled similar numbers of secondary cases generated between versus within camps.

CONCLUSIONS

The consideration of clustered transmission and heterogeneous infectiousness is important for understanding NoV transmission dynamics. Models including these mechanisms may be useful for providing early warning and guiding outbreak response.

Evaluation of 6-Month Versus Continuous Isoniazid Preventive Therapy for Mycobacterium tuberculosis in Adults Living With HIV/AIDS in Malawi

BACKGROUND

To assist the Malawi Ministry of Health to evaluate 2 competing strategies for scale-up of isoniazid preventive therapy (IPT) among HIV-positive adults receiving antiretroviral therapy.

SETTING

Malawi.

METHODS

We used a multidistrict, compartmental model of the Malawi tuberculosis (TB)/HIV epidemic to compare the anticipated health impacts of 6-month versus continuous IPT programs over a 12-year horizon while respecting a US$10.8 million constraint on drug costs in the first 3 years.

RESULTS

The 6-month IPT program could be implemented nationwide, whereas the continuous IPT alternative could be introduced in 14 (of the 27) districts. By the end of year 12, the continuous IPT strategy was predicted to avert more TB cases than the 6-month alternative, although not statistically significant (2368 additional cases averted; 95% projection interval [PI], -1459 to 5023). The 6-month strategy required fewer person-years of IPT to avert a case of TB or death than the continuous strategy. For both programs, the mean reductions in TB incidence among people living with HIV by year 12 were expected to be <10%, and the cumulative numbers of IPT-related hepatotoxicity to exceed the number of all-cause deaths averted in the first 3 years.

CONCLUSIONS

With the given budgetary constraint, the nationwide implementation of 6-month IPT would be more efficient and yield comparable health benefits than implementing a continuous IPT program in fewer districts. The anticipated health effects associated with both IPT strategies suggested that a combination of different TB intervention strategies would likely be required to yield a greater impact on TB control in settings such as Malawi, where antiretroviral therapycoverage is relatively high.

Impact of Hospital Bed Shortages on the Containment of COVID-19 in Wuhan

The global outbreak of COVID-19 has caused worrying concern amongst the public and health authorities. The first and foremost problem that many countries face during the outbreak is a shortage of medical resources. In order to investigate the impact of a shortage of hospital beds on the COVID-19 outbreak, we formulated a piecewise smooth model for describing the limitation of hospital beds. We parameterized the model while using data on the cumulative numbers of confirmed cases, recovered cases, and deaths in Wuhan city from 10 January to 12 April 2020. The results showed that, even with strong prevention and control measures in Wuhan, slowing down the supply rate, reducing the maximum capacity, and delaying the supply time of hospital beds all aggravated the outbreak severity by magnifying the cumulative numbers of confirmed cases and deaths, lengthening the end time of the pandemic, enlarging the value of the effective reproduction number during the outbreak, and postponing the time when the threshold value was reduced to 1. Our results demonstrated that establishment of the Huoshenshan, Leishenshan, and Fangcang shelter hospitals avoided 22,786 people from being infected and saved 6524 lives. Furthermore, the intervention of supplying hospital beds avoided infections in 362,360 people and saved the lives of 274,591 persons. This confirmed that the quick establishment of the Huoshenshan, Leishenshan Hospitals, and Fangcang shelter hospitals, and the designation of other hospitals for COVID-19 patients played important roles in containing the outbreak in Wuhan.

Assessment of the Potential of Vaccination to Combat Antibiotic Resistance in Gonorrhea: A Modeling Analysis to Determine Preferred Product Characteristics

BACKGROUND

Gonorrhea incidence is increasing rapidly in many countries, while antibiotic resistance is making treatment more difficult. Combined with evidence that two meningococcal vaccines are likely partially protective against gonorrhea, this has renewed interest in a gonococcal vaccine, and several candidates are in development. Key questions are how protective and long-lasting a vaccine needs to be, and how to target it. We assessed vaccination's potential impact and the feasibility of achieving the World Health Organization's (WHO) target of reducing gonorrhea incidence by 90% during 2018-2030, by comparing realistic vaccination strategies under a range of scenarios of vaccine efficacy and duration of protection, and emergence of extensively-resistant gonorrhea.

METHODS

We developed a stochastic transmission-dynamic model, incorporating asymptomatic and symptomatic infection and heterogeneous sexual behavior in men who have sex with men (MSM). We used data from England, which has a comprehensive, consistent nationwide surveillance system. Using particle Markov chain Monte Carlo methods, we fitted to gonorrhea incidence in 2008-2017, then used Bayesian forecasting to examine an extensive range of scenarios.

RESULTS

Even in the worst-case scenario of untreatable infection emerging, the WHO target is achievable if all MSM attending sexual health clinics receive a vaccine offering ≥ 52% protection for ≥ 6 years. A vaccine conferring 31% protection (as estimated for MeNZB) for 2-4 years could reduce incidence in 2030 by 45% in the worst-case scenario, and by 75% if > 70% of resistant gonorrhea remains treatable.

CONCLUSIONS

Even a partially-protective vaccine, delivered through a realistic targeting strategy, could substantially reduce gonorrhea incidence, despite antibiotic resistance.

Estimating Transmission Parameters for Respiratory Syncytial Virus and Predicting the Impact of Maternal and Pediatric Vaccination

BACKGROUND

Respiratory syncytial virus (RSV) is a leading cause of respiratory tract illness in young children and a major cause of hospital admissions globally.

METHODS

Here we fit age-structured transmission models with immunity propagation to data from the Netherlands (2012-2017). Data included nationwide hospitalizations with confirmed RSV, general practitioner (GP) data on attendance for care from acute respiratory infection, and virological testing of acute respiratory infections at the GP. The transmission models, equipped with key parameter estimates, were used to predict the impact of maternal and pediatric vaccination.

RESULTS

Estimates of the basic reproduction number were generally high (R0 > 10 in scenarios with high statistical support), while susceptibility was estimated to be low in nonelderly adults (<10% in persons 20-64 years) and was higher in older adults (≥65 years). Scenario analyses predicted that maternal vaccination reduces the incidence of infection in vulnerable infants (<1 year) and shifts the age of first infection from infants to young children.

CONCLUSIONS

Pediatric vaccination is expected to reduce the incidence of infection in infants and young children (0-5 years), slightly increase incidence in 5 to 9-year-old children, and have minor indirect benefits.

Impact of frequent testing on the transmission of HIV and N. gonorrhoeae among men who have sex with men: a mathematical modelling study

OBJECTIVES

To investigate the impact and efficiency of combined testing for HIV and other STIs on HIV and STI transmission among men who have sex with men (MSM) and to assess what subgroups of MSM should be targeted for frequent testing.

METHODS

We developed an agent-based transmission model that simulates infection with HIV or Neisseria gonorrhoeae (NG) among MSM. We examined scenarios with increased percentages of MSM getting tested six monthly, among all MSM or only specific subgroups of MSM (defined according to recent gonorrhoea, number of partners and engagement in condomless anal intercourse (CAI)) and scenarios with reduced intervals between HIV/STI tests.

RESULTS

The most efficient strategies were those with increased percentage of MSM getting tested every 6 months among MSM with a recent gonorrhoea diagnosis; or among MSM who had CAI and ≥10 partners; or MSM who had ≥10 partners. Over 10 years, these strategies resulted in 387-718 averted HIV infections and required 29-164 additional HIV tests per averted HIV infection or one to seven additional gonorrhoea tests per averted NG infection. The most effective strategy in reducing HIV transmission was the one where the intervals between tests were reduced by half, followed by the strategy with increased percentage of MSM getting tested every 6 months among all MSM. Over 10 years, these strategies resulted in 1362 and 1319 averted HIV infections, but required 663 and 584 additional HIV tests per averted HIV infection, respectively.

CONCLUSIONS

Targeting MSM with recent gonorrhoea diagnosis or MSM with many partners is efficient in terms of HIV/STI tests needed to prevent new HIV or NG infections. Major reductions in HIV incidence can be achieved with consistent HIV/STI testing every 6 months among larger groups, including low-risk MSM. To impede HIV transmission, frequent testing should be combined with other prevention measures.

Using the basic reproduction number to assess the risk of transmission of lumpy skin disease virus by biting insects

In recent years, lumpy skin disease virus (LSDV) has emerged as a major threat to cattle outside Africa, where it is endemic. Although evidence suggests that LSDV is transmitted by the bites of blood sucking arthropods, few studies have assessed the risk of transmission posed by particular vector species. Here this risk is assessed by calculating the basic reproduction number (R0 ) for transmission of LSDV by five species of biting insect: the stable fly, Stomoxys calcitrans, the biting midge, Culicoides nubeculosus, and three mosquito species, Aedes aegypti, Anopheles stephensi, and Culex quinquefasciatus. Parameters relating to mechanical transmission of LSDV were estimated using new analyses of previously published data from transmission experiments, while vector life history parameters were derived from the published literature. Uncertainty and sensitivity analyses were used to compute R0 for each species and to identify those parameters which influence its magnitude. Results suggest that S. calcitrans is likely to be the most efficient at transmitting LSDV, with Ae. aegypti also an efficient vector. By contrast, C. nubeculosus, An. stephensi, and Cx. quinquefasciatus are likely to be inefficient vectors of LSDV. However, there is considerable uncertainty associated with the estimates of R0 , reflecting uncertainty in most of the constituent parameters. Sensitivity analysis suggests that future experimental work should focus on estimating the probability of transmission from insect to bovine and on the virus inactivation rate in insects.

Quantifying the consequences of measles-induced immune modulation for whooping cough epidemiology

Measles, an acute viral disease, continues to be an important cause of childhood mortality worldwide. Infection with the measles virus is thought to be associated with a transient but profound period of immune suppression. Recently, it has been claimed that measles-induced immune manipulation lasts for about 30 months and results in increased susceptibility to other co-circulating infectious diseases and more severe disease outcomes upon infection. We tested this hypothesis using model-based inference applied to parallel historical records of measles and whooping cough mortality and morbidity. Specifically, we used maximum likelihood to fit a mechanistic transmission model to incidence data from three different eras, spanning mortality records from 1904 to 1912 and 1922 to 1932 and morbidity records from 1946 to 1956. Our aim was to quantify the timing, severity and pathogenesis impacts of measles-induced immune modulation and their consequences for whooping cough epidemiology across a temporal gradient of measles transmission. We identified an increase in susceptibility to whooping cough following recent measles infection by approximately 85-, 10- and 36-fold for the three eras, respectively, although the duration of this effect was variable. Overall, while the immune impacts of measles may be strong and clearly evident at the individual level, their epidemiological signature in these data appears both modest and inconsistent. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'. This issue is linked with the subsequent theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'.

BOARD INVITED REVIEW: Prospects for improving management of animal disease introductions using disease-dynamic models

Management and policy decisions are continually made to mitigate disease introductions in animal populations despite often limited surveillance data or knowledge of disease transmission processes. Science-based management is broadly recognized as leading to more effective decisions yet application of models to actively guide disease surveillance and mitigate risks remains limited. Disease-dynamic models are an efficient method of providing information for management decisions because of their ability to integrate and evaluate multiple, complex processes simultaneously while accounting for uncertainty common in animal diseases. Here we review disease introduction pathways and transmission processes crucial for informing disease management and models at the interface of domestic animals and wildlife. We describe how disease transmission models can improve disease management and present a conceptual framework for integrating disease models into the decision process using adaptive management principles. We apply our framework to a case study of African swine fever virus in wild and domestic swine to demonstrate how disease-dynamic models can improve mitigation of introduction risk. We also identify opportunities to improve the application of disease models to support decision-making to manage disease at the interface of domestic and wild animals. First, scientists must focus on objective-driven models providing practical predictions that are useful to those managing disease. In order for practical model predictions to be incorporated into disease management a recognition that modeling is a means to improve management and outcomes is important. This will be most successful when done in a cross-disciplinary environment that includes scientists and decision-makers representing wildlife and domestic animal health. Lastly, including economic principles of value-of-information and cost-benefit analysis in disease-dynamic models can facilitate more efficient management decisions and improve communication of model forecasts. Integration of disease-dynamic models into management and decision-making processes is expected to improve surveillance systems, risk mitigations, outbreak preparedness, and outbreak response activities.

Modelling the transmission dynamics of Campylobacter in Ontario, Canada, assuming house flies, Musca domestica, are a mechanical vector of disease transmission

Campylobacter's complicated dynamics and multiple transmission routes have made it difficult to describe using a mathematical framework. Vector-borne disease transmission has been proposed as a potential transmission route of Campylobacter with house flies acting as a mechanical vector. This study aimed to (i) determine if a basic SIR compartment model that included flies as a mechanical vector and incorporated a seasonally forced environment compartment could be used to capture the observed disease dynamics in Ontario, Canada, and (ii) use this model to determine potential changes to campylobacteriosis incidence using predicted changes to fly population size and fly activity under multiple climate change scenarios. The model was fit to 1 year of data and validated against 8 and 12 years of data. It accurately captured the observed incidence. We then explored changes in human disease incidence under multiple climate change scenarios. When fly activity levels were at a 25% increase, our model predicted a 28.15% increase in incidence by 2050 using the medium-low emissions scenario and 30.20% increase using the high emissions scenario. This model demonstrates that the dynamics of Campylobacter transmission can be captured by a model that assumes that the primary transmission of the pathogen occurs via insect vectors.

Metanetwork Transmission Model for Predicting a Malaria-Control Strategy

Background: Mosquitoes are the primary vectors responsible for malaria transmission to humans, with numerous experiments having been conducted to aid in the control of malaria transmission. One of the main approaches aims to develop malaria parasite resistance within the mosquito population by introducing a resistance (R) allele. However, when considering this approach, some critical factors, such as the life of the mosquito, female mosquito fertility capacity, and human and mosquito mobility, have not been considered. Thus, an understanding of how mosquitoes and humans affect disease dynamics is needed to better inform malaria control policymaking. Methods: In this study, a method was proposed to create a metanetwork on the basis of the geographic maps of Gambia, and a model was constructed to simulate evolution within a mixed population, with factors such as birth, death, reproduction, biting, infection, incubation, recovery, and transmission between populations considered in the network metrics. First, the same number of refractory mosquitoes (RR genotype) was introduced into each population, and the prevalence of the R allele (the ratio of resistant alleles to all alleles) and malaria were examined. In addition, a series of simulations were performed to evaluate two different deployment strategies for the reduction of the prevalence of malaria. The R allele and malaria prevalence were calculated for both the strategies, with 10,000 refractory mosquitoes deployed into randomly selected populations or selection based on nodes with top-betweenness values. The 10,000 mosquitoes were deployed among 1, 5, 10, 20, or 40 populations. Results: The simulations in this paper showed that a higher RR genotype (resistant-resistant genes) ratio leads to a higher R allele prevalence and lowers malaria prevalence. Considering the cost of deployment, the simulation was performed with 10,000 refractory mosquitoes deployed among 1 or 5 populations, but this approach did not reduce the original malaria prevalence. Thus, instead, the 10,000 refractory mosquitoes were distributed among 10, 20, or 40 populations and were shown to effectively reduce the original malaria prevalence. Thus, deployment among a relatively small fraction of central nodes can offer an effective strategy to reduce malaria. Conclusion: The standard network centrality measure is suitable for planning the deployment of refractory mosquitoes. Importance: Malaria is an infectious disease that is caused by a plasmodial parasite, and some control strategies have focused on genetically modifying the mosquitoes. This work aims to create a model that takes into account mosquito development and malaria transmission among the population and how these factors influence disease dynamics so as to better inform malaria-control policymaking.

Using paired serology and surveillance data to quantify dengue transmission and control during a large outbreak in Fiji

Dengue is a major health burden, but it can be challenging to examine transmission and evaluate control measures because outbreaks depend on multiple factors, including human population structure, prior immunity and climate. We combined population-representative paired sera collected before and after the 2013/14 dengue-3 outbreak in Fiji with surveillance data to determine how such factors influence transmission and control in island settings. Our results suggested the 10-19 year-old age group had the highest risk of infection, but we did not find strong evidence that other demographic or environmental risk factors were linked to seroconversion. A mathematical model jointly fitted to surveillance and serological data suggested that herd immunity and seasonally varying transmission could not explain observed dynamics. However, the model showed evidence of an additional reduction in transmission coinciding with a vector clean-up campaign, which may have contributed to the decline in cases in the later stages of the outbreak.

Optimal frequency of rabies vaccination campaigns in Sub-Saharan Africa

Rabies causes more than 24 000 human deaths annually in Sub-Saharan Africa. The World Health Organization recommends annual canine vaccination campaigns with at least 70% coverage to control the disease. While previous studies have considered optimal coverage of animal rabies vaccination, variation in the frequency of vaccination campaigns has not been explored. To evaluate the cost-effectiveness of rabies canine vaccination campaigns at varying coverage and frequency, we parametrized a rabies virus transmission model to two districts of northwest Tanzania, Ngorongoro (pastoral) and Serengeti (agro-pastoral). We found that optimal vaccination strategies were every 2 years, at 80% coverage in Ngorongoro and annually at 70% coverage in Serengeti. We further found that the optimality of these strategies was sensitive to the rate of rabies reintroduction from outside the district. Specifically, if a geographically coordinated campaign could reduce reintroduction, vaccination campaigns every 2 years could effectively manage rabies in both districts. Thus, coordinated campaigns may provide monetary savings in addition to public health benefits. Our results indicate that frequency and coverage of canine vaccination campaigns should be evaluated simultaneously and tailored to local canine ecology as well as to the risk of disease reintroduction from surrounding regions.

Is the impact of childhood influenza vaccination less than expected: a transmission modelling study

BACKGROUND

To reduce the burden of severe influenza, most industrialized countries target specific risk-groups with influenza vaccines, e.g. the elderly or individuals with comorbidities. Since children are the main spreaders, some countries have recently implemented childhood vaccination programs to reduce overall virus transmission and thereby influenza disease in the whole population. The introduction of childhood vaccination programs was often supported by modelling studies that predicted substantial incidence reductions. We developed a mathematical transmission model to examine the potential impact of childhood influenza vaccination in Germany, while also challenging established modelling assumptions.

METHODS

We developed an age-stratified SEIR-type transmission model to reproduce the epidemic influenza seasons between 2003/04 and 2013/14. The model was built upon German population counts, contact patterns, and vaccination history and was fitted to seasonal data on influenza-attributable medically attended acute respiratory infections (I-MAARI) and strain distribution using Bayesian methods. As novelties we (i) implemented a stratified model structure enabling seasonal variability and (ii) deviated from the commonly assumed mass-action-principle by employing a phenomenological transmission rate.

RESULTS

According to the model, by vaccinating primarily the elderly over ten seasons 4 million (95% prediction interval: 3.84 - 4.19) I-MAARI were prevented which corresponds to an 8.6% (8.3% - 8.9%) reduction compared to a no-vaccination scenario and a number-needed-to-vaccinate (NNV) to prevent one I-MAARI of 37.1 (35.5 - 38.7). Additional vaccination of 2-10 year-old children at 40% coverage would have led to an overall I-MAARI reduction of 17.8% (17.1 - 18.7%) mostly due to indirect effects with a NNV of 20.7 (19.6 - 21.6). When employing the traditional mass-action-principle, the model predicted a more than 3-fold higher I-MAARI reduction (55.6%) due to childhood vaccination.

CONCLUSION

In Germany, the introduction of routine childhood influenza vaccination could considerably reduce I-MAARI among all age-groups and improve the NNV. However, the predicted impact is much lower compared to previous studies, which is primarily caused by our phenomenological approach to modelling influenza virus transmission.

Member States

The burden of Salmonella entering pig slaughterhouses across the European Union is considered a primary food safety concern. To assist E.U. member states with the development of national control plans, we have developed a farm transmission model applicable to all member states. It is an individual-based stochastic susceptible-infected model that takes into account four different sources of infection of pigs (sows, feed, external contaminants such as rodents, and new stock) and various management practices linked to Salmonella transmission/protection (housing, flooring, feed, all-in-all-out production). A novel development within the model is the assessment of dynamic shedding rates. The results of the model, parameterized for two case study member states (one high and one low prevalence) suggest that breeding herd prevalence is a strong indicator of slaughter pig prevalence. Until a member state's' breeding herd prevalence is brought below 10%, the sow will be the dominant source of infection to pigs raised for meat production; below this level of breeding herd prevalence, feed becomes the dominant force of infection.

Current and future effects of varicella and herpes zoster vaccination in Germany - Insights from a mathematical model in a country with universal varicella vaccination

Varicella zoster virus (VZV) is primarily known for causing varicella in childhood, but can reactivate again as herpes zoster (HZ) after a period of latency, mainly in persons older than 50 years. Universal varicella vaccination was introduced in Germany in 2004, while HZ vaccination has not been recommended yet. We aimed to quantify the potential long-term effects of universal childhood varicella vaccination and HZ vaccination of the elderly on varicella and HZ incidence in Germany over a time horizon of 100 years, using a transmission model calibrated to pre-vaccination data and validated against early post-vaccination data. Using current vaccination coverage rates of 87% (64%) with one (two) varicella vaccine dose(s), the model predicts a decrease in varicella cases by 89% for the year 2015. In the long run, the incidence reduction will stabilize at about 70%. Under the assumption of the boosting hypothesis of improved HZ protection caused by exposure to VZV, the model predicts a temporary increase in HZ incidence of up to 20% for around 50 years. HZ vaccination of the elderly with an assumed coverage of 20% has only limited effects in counteracting this temporary increase in HZ incidence. However, HZ incidence is shown to decrease in the long-term by 58% as vaccinated individuals get older and finally reach age-classes with originally high HZ incidence. Despite substantial uncertainties around several key variables, the model's results provide valuable insights that support decision-making regarding national VZV vaccination strategies.

Influenza A(H7N9) virus transmission between finches and poultry

Transmission via shared water implicates passerine birds as possible vectors for dissemination of this virus.

Low pathogenicity avian influenza A(H7N9) virus has been detected in poultry since 2013, and the virus has caused >450 infections in humans. The mode of subtype H7N9 virus transmission between avian species remains largely unknown, but various wild birds have been implicated as a source of transmission. H7N9 virus was recently detected in a wild sparrow in Shanghai, China, and passerine birds, such as finches, which share space and resources with wild migratory birds, poultry, and humans, can be productively infected with the virus. We demonstrate that interspecies transmission of H7N9 virus occurs readily between society finches and bobwhite quail but only sporadically between finches and chickens. Inoculated finches are better able to infect naive poultry than the reverse. Transmission occurs through shared water but not through the airborne route. It is therefore conceivable that passerine birds may serve as vectors for dissemination of H7N9 virus to domestic poultry.