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.

Towards Evidence-based Control of Opisthorchis viverrini.

Transmission of the carcinogenic liver fluke Opisthorchis viverrini is ongoing across Southeast Asia. Endemic countries within the region are in different stages of achieving control. However, evidence on which interventions are the most effective for reducing parasite transmission, and the resulting liver cancer, is currently lacking. Quantitative modelling can be used to evaluate different control measures against O. viverrini and assist the design of clinical trials. In this article we evaluate the epidemiological parameters that underpin models of O. viverrini and the data necessary for their estimation, with the aim of developing evidence-based strategies for parasite control at a national or regional level.

How modelling can help steer the course set by the World Health Organization 2021-2030 roadmap on neglected tropical diseases.

The World Health Organization recently launched its 2021-2030 roadmap, Ending the Neglect to Attain the Sustainable Development Goals , an updated call to arms to end the suffering caused by neglected tropical diseases. Modelling and quantitative analyses played a significant role in forming these latest goals. In this collection, we discuss the insights, the resulting recommendations and identified challenges of public health modelling for 13 of the target diseases: Chagas disease, dengue, gambiense human African trypanosomiasis (gHAT), lymphatic filariasis (LF), onchocerciasis, rabies, scabies, schistosomiasis, soil-transmitted helminthiases (STH), Taenia solium taeniasis/ cysticercosis, trachoma, visceral leishmaniasis (VL) and yaws. This piece reflects the three cross-cutting themes identified across the collection, regarding the contribution that modelling can make to timelines, programme design, drug development and clinical trials.

The impact of mass drug administration on Schistosoma haematobium infection: what is required to achieve morbidity control and elimination?

BACKGROUND: Schistosomiasis remains an endemic parasitic disease causing much morbidity and, in some cases, mortality. The World Health Organization (WHO) has outlined strategies and goals to combat the burden of disease caused by schistosomiasis. The first goal is morbidity control, which is defined by achieving less than 5% prevalence of heavy intensity infection in school-aged children (SAC). The second goal is elimination as a public health problem (EPHP), achieved when the prevalence of heavy intensity infection in SAC is reduced to less than 1%. Mass drug administration (MDA) of praziquantel is the main strategy for control. However, there is limited availability of praziquantel, particularly in Africa where there is high prevalence of infection. It is therefore important to explore whether the WHO goals can be achieved using the current guidelines for treatment based on targeting SAC and, in some cases, adults. Previous modelling work has largely focused on Schistosoma mansoni, which in advance cases can cause liver and spleen enlargement. There has been much less modelling of the transmission of Schistosoma haematobium, which in severe cases can cause kidney damage and bladder cancer. This lack of modelling has largely been driven by limited data availability and challenges in interpreting these data. RESULTS: In this paper, using an individual-based stochastic model and age-intensity profiles of S. haematobium from two different communities, we calculate the probability of achieving the morbidity and EPHP goals within 15 years of treatment under the current WHO treatment guidelines. We find that targeting SAC only can achieve the morbidity goal for all transmission settings, regardless of the burden of infection in adults. The EPHP goal can be achieved in low transmission settings, but in some moderate to high settings community-wide treatment is needed. CONCLUSIONS: We show that the key determinants of achieving the WHO goals are the precise form of the age-intensity of infection profile and the baseline SAC prevalence. Additionally, we find that the higher the burden of infection in adults, the higher the chances that adults need to be included in the treatment programme to achieve EPHP.

Community-based testing of migrants for infectious diseases (COMBAT-ID): impact, acceptability and cost-effectiveness of identifying infectious diseases among migrants in primary care: protocol for an interrupted time-series, qualitative and health economic analysis.

BACKGROUND: Migration is a major global driver of population change. Certain migrants may be at increased risk of infectious diseases, including tuberculosis (TB), HIV, hepatitis B and hepatitis C, and have poorer outcomes. Early diagnosis and management of these infections can reduce morbidity, mortality and onward transmission and is supported by national guidelines. To date, screening initiatives have been sporadic and focused on individual diseases; systematic routine testing of migrant groups for multiple infections is rarely undertaken and its impact is unknown. We describe the protocol for the evaluation of acceptability, effectiveness and cost-effectiveness of an integrated approach to screening migrants for a range of infectious diseases in primary care. METHODS AND ANALYSIS: We will conduct a mixed-methods study which includes an observational cohort with interrupted time-series analysis before and after the introduction of routine screening of migrants for infectious diseases (latent TB, HIV, hepatitis B and hepatitis C) when first registering with primary care within Leicester, UK. We will assess trends in the monthly number and rate of testing and diagnosis for latent TB, HIV, hepatitis B and hepatitis C to determine the effect of the policy change using segmented regression analyses at monthly time-points. Concurrently, we will undertake an integrated qualitative sub-study to understand the views of migrants and healthcare professionals to the new testing policy in primary care. Finally, we will evaluate the cost-effectiveness of combined infection testing for migrants in primary care. ETHICS AND DISSEMINATION: The study has received HRA and NHS approvals for both the interrupted time-series analysis (16/SC/0127) and the qualitative sub-study (16/EM/0159). For the interrupted time-series analysis we will only use fully anonymised data. For the qualitative sub-study, we will gain written, informed, consent. Dissemination of the results will be through local and national meetings/conferences as well as publications in peer-reviewed journals.

Assessing Strategies Against Gambiense Sleeping Sickness Through Mathematical Modeling.

Background: Control of gambiense sleeping sickness relies predominantly on passive and active screening of people, followed by treatment. Methods: Mathematical modeling explores the potential of 3 complementary interventions in high- and low-transmission settings. Results: Intervention strategies that included vector control are predicted to halt transmission most quickly. Targeted active screening, with better and more focused coverage, and enhanced passive surveillance, with improved access to diagnosis and treatment, are both estimated to avert many new infections but, when used alone, are unlikely to halt transmission before 2030 in high-risk settings. Conclusions: There was general model consensus in the ranking of the 3 complementary interventions studied, although with discrepancies between the quantitative predictions due to differing epidemiological assumptions within the models. While these predictions provide generic insights into improving control, the most effective strategy in any situation depends on the specific epidemiology in the region and the associated costs.

Seasonally timed treatment programs for Ascaris lumbricoides to increase impact-An investigation using mathematical models.

There is clear empirical evidence that environmental conditions can influence Ascaris spp. free-living stage development and host reinfection, but the impact of these differences on human infections, and interventions to control them, is variable. A new model framework reflecting four key stages of the A. lumbricoides life cycle, incorporating the effects of rainfall and temperature, is used to describe the level of infection in the human population alongside the environmental egg dynamics. Using data from South Korea and Nigeria, we conclude that settings with extreme fluctuations in rainfall or temperature could exhibit strong seasonal transmission patterns that may be partially masked by the longevity of A. lumbricoides infections in hosts; we go on to demonstrate how seasonally timed mass drug administration (MDA) could impact the outcomes of control strategies. For the South Korean setting the results predict a comparative decrease of 74.5% in mean worm days (the number of days the average individual spend infected with worms across a 12 month period) between the best and worst MDA timings after four years of annual treatment. The model found no significant seasonal effect on MDA in the Nigerian setting due to a narrower annual temperature range and no rainfall dependence. Our results suggest that seasonal variation in egg survival and maturation could be exploited to maximise the impact of MDA in certain settings.

Identifying English Practices that Are High Antibiotic Prescribers Accounting for Comorbidities and Other Legitimate Medical Reasons for Variation.

BACKGROUND: Seeing one's practice as a high antibiotic prescriber compared to general practices with similar patient populations can be one of the best motivators for change. Current comparisons are based on age-sex weighting of the practice population for expected prescribing rates (STAR-PU). Here, we investigate whether there is a need to additionally account for further potentially legitimate medical reasons for higher antibiotic prescribing. METHODS: Publicly available data from 7376 general practices in England between April 2014 and March 2015 were used. We built two different negative binomial regression models to compare observed versus expected antibiotic dispensing levels per practice: one including comorbidities as covariates and another with the addition of smoking prevalence and deprivation. We compared the ranking of practices in terms of items prescribed per STAR-PU according to i) conventional STAR-PU methodology, ii) observed vs expected prescribing levels using the comorbidity model, and iii) observed vs expected prescribing levels using the full model. FINDINGS: The median number of antibiotic items prescribed per practice per STAR-PU was 1.09 (25th-75th percentile, 0.92-1.25). 1133 practices (76.8% of 1476) were consistently identified as being in the top 20% of high antibiotic prescribers. However, some practices that would be classified as high prescribers using the current STAR-PU methodology would not be classified as high prescribers if comorbidity was accounted for (n = 269, 18.2%) and if additionally smoking prevalence and deprivation were accounted for (n = 312, 21.1%). INTERPRETATION: Current age-sex weighted comparisons of antibiotic prescribing rates in England are fair for many, but not all practices. This new metric that accounts for legitimate medical reasons for higher antibiotic prescribing may have more credibility among general practitioners and, thus, more likely to be acted upon. OUTSTANDING QUESTIONS: Findings of this study indicate that the antibiotic prescribing metric by which practices are measured (and need to implement interventions determined) may be inadequate, and therefore raises the question of how they should be measured. Substantial variation between practices remains after accounting for comorbidities, deprivation and smoking. There is a need for a better understanding of why such variation remains and, more importantly, what can be done to reduce it. While antibiotics are more frequently indicated in patients with comorbidities, it is unclear to what extent antibiotic prescribing can be lowered among that patient population and how this could be achieved.

Cost-effectiveness of screening for HIV in primary care: a health economics modelling analysis.

BACKGROUND: Early HIV diagnosis reduces morbidity, mortality, the probability of onward transmission, and their associated costs, but might increase cost because of earlier initiation of antiretroviral treatment (ART). We investigated this trade-off by estimating the cost-effectiveness of HIV screening in primary care. METHODS: We modelled the effect of the four-times higher diagnosis rate observed in the intervention arm of the RHIVA2 randomised controlled trial done in Hackney, London (UK), a borough with high HIV prevalence (≥0·2% adult prevalence). We constructed a dynamic, compartmental model representing incidence of infection and the effect of screening for HIV in general practices in Hackney. We assessed cost-effectiveness of the RHIVA2 trial by fitting model diagnosis rates to the trial data, parameterising with epidemiological and behavioural data from the literature when required, using trial testing costs and projecting future costs of treatment. FINDINGS: Over a 40 year time horizon, incremental cost-effectiveness ratios were £22 201 (95% credible interval 12 662-132 452) per quality-adjusted life-year (QALY) gained, £372 207 (268 162-1 903 385) per death averted, and £628 874 (434 902-4 740 724) per HIV transmission averted. Under this model scenario, with UK cost data, RHIVA2 would reach the upper National Institute for Health and Care Excellence cost-effectiveness threshold (about £30 000 per QALY gained) after 33 years. Scenarios using cost data from Canada (which indicate prolonged and even higher health-care costs for patients diagnosed late) suggest this threshold could be reached in as little as 13 years. INTERPRETATION: Screening for HIV in primary care has important public health benefits as well as clinical benefits. We predict it to be cost-effective in the UK in the medium term. However, this intervention might be cost-effective far sooner, and even cost-saving, in settings where long-term health-care costs of late-diagnosed patients in high-prevalence regions are much higher (≥60%) than those of patients diagnosed earlier. Screening for HIV in primary care is cost-effective and should be promoted. FUNDING: NHS City and Hackney, UK Department of Health, National Institute for Health Research Collaboration for Leadership in Applied Health Research and Care.

Innovative tools and approaches to end the transmission of Mycobacterium leprae.

Leprosy control has seen little innovation and only limited progress in the past decade. However, research on the disease has increased and important innovations are underway. Here, we comment on efforts to develop tools and approaches to detect leprosy and to stop the transmission of Mycobacterium leprae, the causative bacillus of the disease. The tracing and screening of contacts of known patients with leprosy promises to strengthen early diagnosis, while preventive chemotherapy will reduce the risk of contacts developing the disease by 50-60% within 2 years of administration. Until now, diagnosis has been mainly based on the presence of signs and symptoms, but efforts are underway to develop inexpensive, reliable, point-of-care tests to diagnose infection. Development of a leprosy-specific vaccine that boosts long-lasting T-cell responses is also a research objective. As for launching a programme to interrupt transmission, two interlinked tools-epidemiological modelling and the concept of an investment case-are being developed to explore the feasibility and costs of such a programme and its overall effect on individuals and society. We believe that sustained innovation is needed and that only a combination of tools and approaches holds promise to end M leprae transmission.

Development and evaluation of a Markov model to predict changes in schistosomiasis prevalence in response to praziquantel treatment: a case study of Schistosoma mansoni in Uganda and Mali.

BACKGROUND: Understanding whether schistosomiasis control programmes are on course to control morbidity and potentially switch towards elimination interventions would benefit from user-friendly quantitative tools that facilitate analysis of progress and highlight areas not responding to treatment. This study aimed to develop and evaluate such a tool using large datasets collected during Schistosomiasis Control Initiative-supported control programmes. METHODS: A discrete-time Markov model was developed using transition probability matrices parameterized with control programme longitudinal data on Schistosoma mansoni obtained from Uganda and Mali. Four matrix variants (A-D) were used to compare different data types for parameterization: A-C from Uganda and D from Mali. Matrix A used data at baseline and year 1 of the control programme; B used year 1 and year 2; C used baseline and year 1 from selected districts, and D used baseline and year 1 Mali data. Model predictions were tested against 3 subsets of the Uganda dataset: dataset 1, the full 4-year longitudinal cohort; dataset 2, from districts not used to parameterize matrix C; dataset 3, cross-sectional data, and dataset 4, from Mali as an independent dataset. RESULTS: The model parameterized using matrices A, B and D predicted similar infection dynamics (overall and when stratified by infection intensity). Matrices A-D successfully predicted prevalence in each follow-up year for low and high intensity categories in dataset 1 followed by dataset 2. Matrices A, B and D yielded similar and close matches to dataset 1 with marginal discrepancies when comparing model outputs against datasets 2 and 3. Matrix C produced more variable results, correctly estimating fewer data points. CONCLUSION: Model outputs closely matched observed values and were a useful predictor of the infection dynamics of S. mansoni when using longitudinal and cross-sectional data from Uganda. This also held when the model was tested with data from Mali. This was most apparent when modelling overall infection and in low and high infection intensity areas. Our results indicate the applicability of this Markov model approach as countries aim at reaching their control targets and potentially move towards the elimination of schistosomiasis.