Determining the optimal strategies to achieve elimination of transmission for Schistosoma mansoni.

BACKGROUND: In January 2021, the World Health Organization published the 2021-2030 roadmap for the control of neglected tropical diseases (NTDs). The goal for schistosomiasis is to achieve elimination as a public health problem (EPHP) and elimination of transmission (EOT) in 78 and 25 countries (by 2030), respectively. Mass drug administration (MDA) of praziquantel continues to be the main strategy for control and elimination. However, as there is limited availability of praziquantel, it is important to determine what volume of treatments are required, who should be targeted and how frequently treatment must be administered to eliminate either transmission or morbidity caused by infection in different endemic settings with varied transmission intensities. METHODS AND RESULTS: In this paper, we employ two individual-based stochastic models of schistosomiasis transmission developed independently by the Imperial College London (ICL) and University of Oxford (SCHISTOX) to determine the optimal treatment strategies to achieve EOT. We find that treating school-age children (SAC) only is not sufficient to achieve EOT within a feasible time frame, regardless of the transmission setting and observed age-intensity of infection profile. Both models show that community-wide treatment is necessary to interrupt transmission in all endemic settings with low, medium and high pristine transmission intensities. CONCLUSIONS: The required MDA coverage level to achieve either transmission or morbidity elimination depends on the prevalence prior to the start of treatment and the burden of infection in adults. The higher the worm burden in adults, the higher the coverage levels required for this age category through community-wide treatment programmes. Therefore, it is important that intensity and prevalence data are collected in each age category, particularly from SAC and adults, so that the correct coverage level can be calculated and administered.

The impact of active case finding on transmission dynamics of tuberculosis: A modelling study.

BACKGROUND: In the last decade, active case finding (ACF) strategies for tuberculosis (TB) have been implemented in many diverse settings, with some showing large increases in case detection and reporting at the sub-national level. There have also been several studies which seek to provide evidence for the benefits of ACF to individuals and communities in the broader context. However, there remains no quantification of the impact of ACF with regards to reducing the burden of transmission. We sought to address this knowledge gap and quantify the potential impact of active case finding on reducing transmission of TB at the national scale and further, to determine the intensification of intervention efforts required to bring the reproduction number (R0) below 1 for TB. METHODS: We adopt a dynamic transmission model that incorporates heterogeneity in risk to TB to assess the impact of an ACF programme (IMPACT TB) on reducing TB incidence in Vietnam and Nepal. We fit the models to country-level incidence data using a Bayesian Markov Chain Monte Carlo approach. We assess the impact of ACF using a parameter in our model, which we term the treatment success rate. Using programmatic data, we estimate how much this parameter has increased as a result of IMPACT TB in the implementation districts of Vietnam and Nepal and quantify additional efforts needed to eliminate transmission of TB in these countries by 2035. RESULTS: Extending the IMPACT TB programme to national coverage would lead to moderate decreases in TB incidence and would not be enough to interrupt transmission by 2035. Decreasing transmission sufficiently to bring the reproduction number (R0) below 1, would require a further intensification of current efforts, even at the sub-national level. CONCLUSIONS: Active case finding programmes are effective in reducing TB in the short term. However, interruption of transmission in high-burden countries, like Vietnam and Nepal, will require comprehensive incremental efforts. Complementary measures to reduce progression from infection to disease, and reactivation of latent infection, are needed to meet the WHO End TB incidence targets.

Gender-related differences in prevalence, intensity and associated risk factors of Schistosoma infections in Africa: A systematic review and meta-analysis.

BACKGROUND: Schistosomiasis remains a global-health problem with over 90% of its burden concentrated in Africa. Field studies reflect the complex ways in which socio-cultural and socio-economic variables, affect the distribution of Schistosoma infections across different populations. This review set out to systematically investigate and quantify the differences in Schistosoma infection burdens between males and females in Africa for two of the most prevalent Schistosoma species-Schistosoma mansoni and Schistosoma haematobium. METHODOLOGY: We searched (from inception to 11th March 2020) Embase, MEDLINE, PubMed, and Web of Science for relevant studies on schistosomiasis. We included studies that report S. mansoni and/or S. haematobium prevalence and/or intensity data distributed between males and females. We conducted meta-analyses on the male to female (M:F) prevalence of infection ratios. Subgroup analyses were performed according to study baseline prevalence, sample size and the lower and upper age limit of study participants. We also present a descriptive analysis of differential risk and intensity of infection across males and females. Evidence for differences in the prevalence of schistosomiasis infection between males and females is presented, stratified by Schistosoma species. RESULT: We identified 128 relevant studies, with over 200,000 participants across 23 countries. Of all the reported differences in the prevalence of infection between males and females, only 41% and 34% were statistically significant for S. mansoni and S. haematobium, respectively. Similar proportions of studies (27% and 34% for for S. haematobium and S. mansoni, respectively) of the reported differences in intensity of infection between males and females were statistically significant. The meta-analyses summarized a higher prevalence of infection in males; pooled random-effects weighted M:F prevalence of infection ratios were 1.20 (95% CI 1.11-1.29) for S. haematobium and 1.15 (95% CI 1.08-1.22) for S. mansoni. However, females are underrespresented in some of the studies. Additionally, there was significant heterogeneity across studies (Higgins I2 statistic (p-values < 0.001, I2values>95%)). Results of the subgroup analysis showed that the baseline prevalence influenced the M:F prevalence ratios for S. haematobium and S. mansoni, with higher M:F prevalence of infection ratios in settings with a lower baseline prevalence of infection. Across the studies, we identified four major risk factors associated with infection rates: occupational and recreational water contact, knowledge, socio-economic factors and demographic factors. The effect of these risk factors on the burden of infection in males and females varied across studies. CONCLUSIONS: We find evidence of differences in prevalence of infection between males and females which may reflect differences in gender norms and water contact activities, suggesting that policy changes at the regional level may help ameliorate gender-related disparities in schistosomiasis infection burden. Collecting, robustly analysing, and reporting, sex-disaggregated epidemiological data, is currently lacking, but would be highly informative for planning effective treatment programmes and establishing those most at risk of schistosomiasis infections.

Contact tracing is an imperfect tool for controlling COVID-19 transmission and relies on population adherence.

Emerging evidence suggests that contact tracing has had limited success in the UK in reducing the R number across the COVID-19 pandemic. We investigate potential pitfalls and areas for improvement by extending an existing branching process contact tracing model, adding diagnostic testing and refining parameter estimates. Our results demonstrate that reporting and adherence are the most important predictors of programme impact but tracing coverage and speed plus diagnostic sensitivity also play an important role. We conclude that well-implemented contact tracing could bring small but potentially important benefits to controlling and preventing outbreaks, providing up to a 15% reduction in R. We reaffirm that contact tracing is not currently appropriate as the sole control measure.

Engagement and adherence trade-offs for SARS-CoV-2 contact tracing.

Contact tracing is an important tool for allowing countries to ease lockdown policies introduced to combat SARS-CoV-2. For contact tracing to be effective, those with symptoms must self-report themselves while their contacts must self-isolate when asked. However, policies such as legal enforcement of self-isolation can create trade-offs by dissuading individuals from self-reporting. We use an existing branching process model to examine which aspects of contact tracing adherence should be prioritized. We consider an inverse relationship between self-isolation adherence and self-reporting engagement, assuming that increasingly strict self-isolation policies will result in fewer individuals self-reporting to the programme. We find that policies which increase the average duration of self-isolation, or that increase the probability that people self-isolate at all, at the expense of reduced self-reporting rate, will not decrease the risk of a large outbreak and may increase the risk, depending on the strength of the trade-off. These results suggest that policies to increase self-isolation adherence should be implemented carefully. Policies that increase self-isolation adherence at the cost of self-reporting rates should be avoided. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'.

Dynamics of SARS-CoV-2 with waning immunity in the UK population.

The dynamics of immunity are crucial to understanding the long-term patterns of the SARS-CoV-2 pandemic. Several cases of reinfection with SARS-CoV-2 have been documented 48-142 days after the initial infection and immunity to seasonal circulating coronaviruses is estimated to be shorter than 1 year. Using an age-structured, deterministic model, we explore potential immunity dynamics using contact data from the UK population. In the scenario where immunity to SARS-CoV-2 lasts an average of three months for non-hospitalized individuals, a year for hospitalized individuals, and the effective reproduction number after lockdown ends is 1.2 (our worst-case scenario), we find that the secondary peak occurs in winter 2020 with a daily maximum of 387 000 infectious individuals and 125 000 daily new cases; threefold greater than in a scenario with permanent immunity. Our models suggest that longitudinal serological surveys to determine if immunity in the population is waning will be most informative when sampling takes place from the end of the lockdown in June until autumn 2020. After this period, the proportion of the population with antibodies to SARS-CoV-2 is expected to increase due to the secondary wave. Overall, our analysis presents considerations for policy makers on the longer-term dynamics of SARS-CoV-2 in the UK and suggests that strategies designed to achieve herd immunity may lead to repeated waves of infection as immunity to reinfection is not permanent. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'.

Maintaining Low Prevalence of Schistosoma mansoni: Modeling the Effect of Less Frequent Treatment.

BACKGROUND: The World Health Organization previously set goals of controlling morbidity due to schistosomiasis by 2020 and attaining elimination as a public health problem (EPHP) by 2025 (now adjusted to 2030 in the new neglected tropical diseases roadmap). As these milestones are reached, it is important that programs reassess their treatment strategies to either maintain these goals or progress from morbidity control to EPHP and ultimately to interruption of transmission. In this study, we consider different mass drug administration (MDA) strategies to maintain the goals. METHODS: We used 2 independently developed, individual-based stochastic models of schistosomiasis transmission to assess the optimal treatment strategy of a multiyear program to maintain the morbidity control and the EPHP goals. RESULTS: We found that, in moderate-prevalence settings, once the morbidity control and EPHP goals are reached it may be possible to maintain the goals using less frequent MDAs than those that are required to achieve the goals. On the other hand, in some high-transmission settings, if control efforts are reduced after achieving the goals, particularly the morbidity control goal, there is a high chance of recrudescence. CONCLUSIONS: To reduce the risk of recrudescence after the goals are achieved, programs have to re-evaluate their strategies and decide to either maintain these goals with reduced efforts where feasible or continue with at least the same efforts required to reach the goals.

SCHISTOX: An individual based model for the epidemiology and control of schistosomiasis.

A stochastic individual based model, SCHISTOX, has been developed for the study of schistosome transmission dynamics and the impact of control by mass drug administration. More novel aspects that can be investigated include individual level adherence and access to treatment, multiple communities, human sex population dynamics, and implementation of a potential vaccine. Many of the model parameters have been estimated within previous studies and have been shown to vary between communities, such as the age-specific contact rates governing the age profiles of infection. However, uncertainty remains as there are wide ranges for certain parameter values and a few remain relatively unknown. We analyse the model dynamics by parameterizing it with published parameter values. We also discuss the development of SCHISTOX in the form of a publicly available open-source GitHub repository. The next key development stage involves validating the model by calibrating to epidemiological data.

Disruptions to schistosomiasis programmes due to COVID-19: an analysis of potential impact and mitigation strategies.

BACKGROUND: The 2030 goal for schistosomiasis is elimination as a public health problem (EPHP), with mass drug administration (MDA) of praziquantel to school-age children (SAC) as a central pillar of the strategy. However, due to coronavirus disease 2019, many mass treatment campaigns for schistosomiasis have been halted, with uncertain implications for the programmes. METHODS: We use mathematical modelling to explore how postponement of MDA and various mitigation strategies affect achievement of the EPHP goal for Schistosoma mansoni and S. haematobium. RESULTS: For both S. mansoni and S. haematobium in moderate- and some high-prevalence settings, the disruption may delay the goal by up to 2 y. In some high-prevalence settings, EPHP is not achievable with current strategies and so the disruption will not impact this. Here, increasing SAC coverage and treating adults can achieve the goal. The impact of MDA disruption and the appropriate mitigation strategy varies according to the baseline prevalence prior to treatment, the burden of infection in adults and the stage of the programme. CONCLUSIONS: Schistosomiasis MDA programmes in medium- and high-prevalence areas should restart as soon as is feasible and mitigation strategies may be required in some settings.

Predicted Impact of COVID-19 on Neglected Tropical Disease Programs and the Opportunity for Innovation.

Due to the COVID-19 pandemic, many key neglected tropical disease (NTD) activities have been postponed. This hindrance comes at a time when the NTDs are progressing towards their ambitious goals for 2030. Mathematical modelling on several NTDs, namely gambiense sleeping sickness, lymphatic filariasis, onchocerciasis, schistosomiasis, soil-transmitted helminthiases (STH), trachoma, and visceral leishmaniasis, shows that the impact of this disruption will vary across the diseases. Programs face a risk of resurgence, which will be fastest in high-transmission areas. Furthermore, of the mass drug administration diseases, schistosomiasis, STH, and trachoma are likely to encounter faster resurgence. The case-finding diseases (gambiense sleeping sickness and visceral leishmaniasis) are likely to have fewer cases being detected but may face an increasing underlying rate of new infections. However, once programs are able to resume, there are ways to mitigate the impact and accelerate progress towards the 2030 goals.

Introducing risk inequality metrics in tuberculosis policy development.

Global stakeholders including the World Health Organization rely on predictive models for developing strategies and setting targets for tuberculosis care and control programs. Failure to account for variation in individual risk leads to substantial biases that impair data interpretation and policy decisions. Anticipated impediments to estimating heterogeneity for each parameter are discouraging despite considerable technical progress in recent years. Here we identify acquisition of infection as the single process where heterogeneity most fundamentally impacts model outputs, due to selection imposed by dynamic forces of infection. We introduce concrete metrics of risk inequality, demonstrate their utility in mathematical models, and pack the information into a risk inequality coefficient (RIC) which can be calculated and reported by national tuberculosis programs for use in policy development and modeling.

Genome-based transmission modelling separates imported tuberculosis from recent transmission within an immigrant population.

In many countries the incidence of tuberculosis (TB) is low and is largely shaped by immigrant populations from high-burden countries. This is the case in Norway, where more than 80 % of TB cases are found among immigrants from high-incidence countries. A variable latent period, low rates of evolution and structured social networks make separating import from within-border transmission a major conundrum to TB control efforts in many low-incidence countries. Clinical Mycobacterium tuberculosis isolates belonging to an unusually large genotype cluster associated with people born in the Horn of Africa have been identified in Norway over the last two decades. We modelled transmission based on whole-genome sequence data to estimate infection times for individual patients. By contrasting these estimates with time of arrival in Norway, we estimate on a case-by-case basis whether patients were likely to have been infected before or after arrival. Independent import was responsible for the majority of cases, but we estimate that about one-quarter of the patients had contracted TB in Norway. This study illuminates the transmission dynamics within an immigrant community. Our approach is broadly applicable to many settings where TB control programmes can benefit from understanding when and where patients acquired TB.

Convergent evolution and topologically disruptive polymorphisms among multidrug-resistant tuberculosis in Peru.

BACKGROUND: Multidrug-resistant tuberculosis poses a major threat to the success of tuberculosis control programs worldwide. Understanding how drug-resistant tuberculosis evolves can inform the development of new therapeutic and preventive strategies. METHODS: Here, we use novel genome-wide analysis techniques to identify polymorphisms that are associated with drug resistance, adaptive evolution and the structure of the phylogenetic tree. A total of 471 samples from different patients collected between 2009 and 2013 in the Lima suburbs of Callao and Lima South were sequenced on the Illumina MiSeq platform with 150bp paired-end reads. After alignment to the reference H37Rv genome, variants were called using standardized methodology. Genome-wide analysis was undertaken using custom written scripts implemented in R software. RESULTS: High quality homoplastic single nucleotide polymorphisms were observed in genes known to confer drug resistance as well as genes in the Mycobacterium tuberculosis ESX secreted protein pathway, pks12, and close to toxin/anti-toxin pairs. Correlation of homoplastic variant sites identified that many were significantly correlated, suggestive of epistasis. Variation in genes coding for ESX secreted proteins also significantly disrupted phylogenetic structure. Mutations in ESX genes in key antigenic epitope positions were also found to disrupt tree topology. CONCLUSION: Variation in these genes have a biologically plausible effect on immunogenicity and virulence. This makes functional characterization warranted to determine the effects of these polymorphisms on bacterial fitness and transmission.

Diverse drug-resistant subpopulations of Mycobacterium tuberculosis are sustained in continuous culture.

Drug resistance to tuberculosis (TB) has become more widespread over the past decade. As such, understanding the emergence and fitness of antibiotic-resistant subpopulations is crucial for the development of new interventions. Here we use a simple mathematical model to explain the differences in the response to isoniazid (INH) of Mycobacterium tuberculosis cells cultured under two growth rates in a chemostat. We obtain posterior distributions of model parameters consistent with data using a Markov chain Monte Carlo (MCMC) method. We explore the dynamics of diverse INH-resistant subpopulations consistent with these data in a multi-population model. We find that the simple model captures the qualitative behaviour of the cultures under both dilution rates and also present testable predictions about how diversity is maintained in such cultures.

Competition, coinfection and strain replacement in models of Bordetella pertussis.

Pertussis, or whooping cough, is an important respiratory infection causing considerable infant mortality worldwide. Recently, incidence has risen in countries with strong vaccine programmes and there are concerns about antigenic shift resulting in vaccine evasion. Interactions between pertussis and non-vaccine-preventable strains will play an important role in the evolution and population dynamics of pertussis. In particular, if we are to understand the role strain replacement plays in vaccinated settings, it will be essential to understand how strains or variants of pertussis interact. Here we explore under what conditions we would expect strain replacement to be of concern in pertussis. We develop a dynamic transmission model that allows for coinfection between Bordetella pertussis (the main causative agent of pertussis) and a strain or variant unaffected by the vaccine. We incorporate both neutrality (in the sense of ecological/population genetic neutrality) and immunity into the model, leaving the specificity of the immune response flexible. We find that strain replacement may be considerable when immunity is non-specific. This is in contrast to previous findings where neutrality was not considered. We conclude that the extent to which models reflect ecological neutrality can have a large impact on conclusions regarding strain replacement. This will likely have onward consequences for estimates of vaccine efficacy and cost-effectiveness.