Long-term vaccination strategies to mitigate the impact of SARS-CoV-2 transmission: A modelling study.

BACKGROUND: Vaccines have reduced severe disease and death from Coronavirus Disease 2019 (COVID-19). However, with evidence of waning efficacy coupled with continued evolution of the virus, health programmes need to evaluate the requirement for regular booster doses, considering their impact and cost-effectiveness in the face of ongoing transmission and substantial infection-induced immunity. METHODS AND FINDINGS: We developed a combined immunological-transmission model parameterised with data on transmissibility, severity, and vaccine effectiveness. We simulated Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) transmission and vaccine rollout in characteristic global settings with different population age-structures, contact patterns, health system capacities, prior transmission, and vaccine uptake. We quantified the impact of future vaccine booster dose strategies with both ancestral and variant-adapted vaccine products, while considering the potential future emergence of new variants with modified transmission, immune escape, and severity properties. We found that regular boosting of the oldest age group (75+) is an efficient strategy, although large numbers of hospitalisations and deaths could be averted by extending vaccination to younger age groups. In countries with low vaccine coverage and high infection-derived immunity, boosting older at-risk groups was more effective than continuing primary vaccination into younger ages in our model. Our study is limited by uncertainty in key parameters, including the long-term durability of vaccine and infection-induced immunity as well as uncertainty in the future evolution of the virus. CONCLUSIONS: Our modelling suggests that regular boosting of the high-risk population remains an important tool to reduce morbidity and mortality from current and future SARS-CoV-2 variants. Our results suggest that focusing vaccination in the highest-risk cohorts will be the most efficient (and hence cost-effective) strategy to reduce morbidity and mortality.

Estimating long-term vaccine effectiveness against SARS-CoV-2 variants: a model-based approach.

With the ongoing evolution of the SARS-CoV-2 virus updated vaccines may be needed. We fitted a model linking immunity levels and protection to vaccine effectiveness data from England for three vaccines (Oxford/AstraZeneca AZD1222, Pfizer-BioNTech BNT162b2, Moderna mRNA-1273) and two variants (Delta, Omicron). Our model reproduces the observed sustained protection against hospitalisation and death from the Omicron variant over the first six months following dose 3 with the ancestral vaccines but projects a gradual waning to moderate protection after 1 year. Switching the fourth dose to a variant-matched vaccine against Omicron BA.1/2 is projected to prevent nearly twice as many hospitalisations and deaths over a 1-year period compared to administering the ancestral vaccine. This result is sensitive to the degree to which immunogenicity data can be used to predict vaccine effectiveness and uncertainty regarding the impact that infection-induced immunity (not captured here) may play in modifying future vaccine effectiveness.

Evaluating and mitigating the potential indirect effect of COVID-19 on control programmes for seven neglected tropical diseases: a modelling study.

BACKGROUND: In line with movement restrictions and physical distancing essential for the control of the COVID-19 pandemic, WHO recommended postponement of all neglected tropical disease (NTD) control activities that involve community-based surveys, active case finding, and mass drug administration in April, 2020. Following revised guidance later in 2020, and after interruptions to NTD programmes of varying lengths, NTD programmes gradually restarted in the context of an ongoing pandemic. However, ongoing challenges and service gaps have been reported. This study aimed to evaluate the potential effect of the programmatic interruptions and strategies to mitigate this effect. METHODS: For seven NTDs, namely soil-transmitted helminths, schistosomiasis, lymphatic filariasis, onchocerciasis, trachoma, visceral leishmaniasis, and human African trypanosomiasis, we used mathematical transmission models to simulate the effect of programme interruptions on the dynamics of each of these diseases in different endemic settings. We also explored the potential benefit of implementing mitigation strategies, primarily in terms of minimising the delays to control targets. FINDINGS: We show that the effect of the COVID-19-induced interruption in terms of delay to achieving elimination goals might in some cases be much longer than the duration of the interruption. For schistosomiasis, onchocerciasis, trachoma, and visceral leishmaniasis, a mean delay of 2-3 years for a 1-year interruption is predicted in areas of highest prevalence. We also show that these delays can largely be mitigated by measures such as additional mass drug administration or enhanced case-finding. INTERPRETATION: The COVID-19 pandemic has brought infectious disease control to the forefront of global consciousness. It is essential that the NTDs, so long neglected in terms of research and financial support, are not overlooked, and remain a priority in health service planning and funding. FUNDING: Bill & Melinda Gates Foundation, Medical Research Council, and the UK Foreign, Commonwealth & Development Office.

COVID-19 impact on routine immunisations for vaccine-preventable diseases: Projecting the effect of different routes to recovery.

Over the past two decades, vaccination programmes for vaccine-preventable diseases (VPDs) have expanded across low- and middle-income countries (LMICs). However, the rise of COVID-19 resulted in global disruption to routine immunisation activities. Such disruptions could have a detrimental effect on public health, leading to more deaths from VPDs, particularly without mitigation efforts. Hence, as routine immunisation activities resume, it is important to estimate the effectiveness of different approaches for recovery. We apply an impact extrapolation method developed by the Vaccine Impact Modelling Consortium to estimate the impact of COVID-19-related disruptions with different recovery scenarios for ten VPDs across 112 LMICs. We focus on deaths averted due to routine immunisations occurring in the years 2020-2030 and investigate two recovery scenarios relative to a no-COVID-19 scenario. In the recovery scenarios, we assume a 10% COVID-19-related drop in routine immunisation coverage in the year 2020. We then linearly interpolate coverage to the year 2030 to investigate two routes to recovery, whereby the immunization agenda (IA2030) targets are reached by 2030 or fall short by 10%. We estimate that falling short of the IA2030 targets by 10% leads to 11.26% fewer fully vaccinated persons (FVPs) and 11.34% more deaths over the years 2020-2030 relative to the no-COVID-19 scenario, whereas, reaching the IA2030 targets reduces these proportions to 5% fewer FVPs and 5.22% more deaths. The impact of the disruption varies across the VPDs with diseases where coverage expands drastically in future years facing a smaller detrimental effect. Overall, our results show that drops in routine immunisation coverage could result in more deaths due to VPDs. As the impact of COVID-19-related disruptions is dependent on the vaccination coverage that is achieved over the coming years, the continued efforts of building up coverage and addressing gaps in immunity are vital in the road to recovery.

Vaccine equity in low and middle income countries: a systematic review and meta-analysis.

BACKGROUND: Evidence to date has shown that inequality in health, and vaccination coverage in particular, can have ramifications to wider society. However, whilst individual studies have sought to characterise these heterogeneities in immunisation coverage at national level, few have taken a broad and quantitative view of the contributing factors to heterogeneity in immunisation coverage and impact, i.e. the number of cases, deaths, and disability-adjusted life years averted. This systematic review aims to highlight these geographic, demographic, and sociodemographic characteristics through a qualitative and quantitative approach, vital to prioritise and optimise vaccination policies. METHODS: A systematic review of two databases (PubMed and Web of Science) was undertaken using search terms and keywords to identify studies examining factors on immunisation inequality and heterogeneity in vaccination coverage. Inclusion criteria were applied independently by two researchers. Studies including data on key characteristics of interest were further analysed through a meta-analysis to produce a pooled estimate of the risk ratio using a random effects model for that characteristic. RESULTS: One hundred and eight studies were included in this review. We found that inequalities in wealth, education, and geographic access can affect vaccine impact and vaccination dropout. We estimated those living in rural areas were not significantly different in terms of full vaccination status compared to urban areas but noted considerable heterogeneity between countries. We found that females were 3% (95%CI[1%, 5%]) less likely to be fully vaccinated than males. Additionally, we estimated that children whose mothers had no formal education were 28% (95%CI[18%,47%]) less likely to be fully vaccinated than those whose mother had primary level, or above, education. Finally, we found that individuals in the poorest wealth quintile were 27% (95%CI [16%,37%]) less likely to be fully vaccinated than those in the richest. CONCLUSIONS: We found a nuanced picture of inequality in vaccination coverage and access with wealth disparity dominating, and likely driving, other disparities. This review highlights the complex landscape of inequity and further need to design vaccination strategies targeting missed subgroups to improve and recover vaccination coverage following the COVID-19 pandemic. TRIAL REGISTRATION: Prospero, CRD42021261927.

Global impact of the first year of COVID-19 vaccination: a mathematical modelling study.

BACKGROUND: The first COVID-19 vaccine outside a clinical trial setting was administered on Dec 8, 2020. To ensure global vaccine equity, vaccine targets were set by the COVID-19 Vaccines Global Access (COVAX) Facility and WHO. However, due to vaccine shortfalls, these targets were not achieved by the end of 2021. We aimed to quantify the global impact of the first year of COVID-19 vaccination programmes. METHODS: A mathematical model of COVID-19 transmission and vaccination was separately fit to reported COVID-19 mortality and all-cause excess mortality in 185 countries and territories. The impact of COVID-19 vaccination programmes was determined by estimating the additional lives lost if no vaccines had been distributed. We also estimated the additional deaths that would have been averted had the vaccination coverage targets of 20% set by COVAX and 40% set by WHO been achieved by the end of 2021. FINDINGS: Based on official reported COVID-19 deaths, we estimated that vaccinations prevented 14·4 million (95% credible interval [Crl] 13·7-15·9) deaths from COVID-19 in 185 countries and territories between Dec 8, 2020, and Dec 8, 2021. This estimate rose to 19·8 million (95% Crl 19·1-20·4) deaths from COVID-19 averted when we used excess deaths as an estimate of the true extent of the pandemic, representing a global reduction of 63% in total deaths (19·8 million of 31·4 million) during the first year of COVID-19 vaccination. In COVAX Advance Market Commitment countries, we estimated that 41% of excess mortality (7·4 million [95% Crl 6·8-7·7] of 17·9 million deaths) was averted. In low-income countries, we estimated that an additional 45% (95% CrI 42-49) of deaths could have been averted had the 20% vaccination coverage target set by COVAX been met by each country, and that an additional 111% (105-118) of deaths could have been averted had the 40% target set by WHO been met by each country by the end of 2021. INTERPRETATION: COVID-19 vaccination has substantially altered the course of the pandemic, saving tens of millions of lives globally. However, inadequate access to vaccines in low-income countries has limited the impact in these settings, reinforcing the need for global vaccine equity and coverage. FUNDING: Schmidt Science Fellowship in partnership with the Rhodes Trust; WHO; UK Medical Research Council; Gavi, the Vaccine Alliance; Bill & Melinda Gates Foundation; National Institute for Health Research; and Community Jameel.

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.

How can the public health impact of vaccination be estimated?

BACKGROUND: Deaths due to vaccine preventable diseases cause a notable proportion of mortality worldwide. To quantify the importance of vaccination, it is necessary to estimate the burden averted through vaccination. The Vaccine Impact Modelling Consortium (VIMC) was established to estimate the health impact of vaccination. METHODS: We describe the methods implemented by the VIMC to estimate impact by calendar year, birth year and year of vaccination (YoV). The calendar and birth year methods estimate impact in a particular year and over the lifetime of a particular birth cohort, respectively. The YoV method estimates the impact of a particular year's vaccination activities through the use of impact ratios which have no stratification and stratification by activity type and/or birth cohort. Furthermore, we detail an impact extrapolation (IE) method for use between coverage scenarios. We compare the methods, focusing on YoV for hepatitis B, measles and yellow fever. RESULTS: We find that the YoV methods estimate similar impact with routine vaccinations but have greater yearly variation when campaigns occur with the birth cohort stratification. The IE performs well for the YoV methods, providing a time-efficient mechanism for updates to impact estimates. CONCLUSIONS: These methods provide a robust set of approaches to quantify vaccination impact; however it is vital that the area of impact estimation continues to develop in order to capture the full effect of immunisation.

Are current preventive chemotherapy strategies for controlling and eliminating neglected tropical diseases cost-effective?

Neglected tropical diseases (NTDs) remain a significant cause of morbidity and mortality in many low-income and middle-income countries. Several NTDs, namely lymphatic filariasis, onchocerciasis, schistosomiasis, soil-transmitted helminthiases (STH) and trachoma, are predominantly controlled by preventive chemotherapy (or mass drug administration), following recommendations set by the WHO. Over one billion people are now treated for NTDs with this strategy per year. However, further investment and increased domestic healthcare spending are urgently needed to continue these programmes. Consequently, it is vital that the cost-effectiveness of preventive chemotherapy is understood. We analyse the current estimates on the cost per disability-adjusted life year (DALY) of the preventive chemotherapy strategies predominantly used for these diseases and identify key evidence gaps that require further research. Overall, the reported estimates show that preventive chemotherapy is generally cost-effective, supporting WHO recommendations. More specifically, the cost per DALY averted estimates relating to community-wide preventive chemotherapy for lymphatic filariasis and onchocerciasis were particularly favourable when compared with other public health interventions. Cost per DALY averted estimates of school-based preventive chemotherapy for schistosomiasis and STH were also generally favourable but more variable. Notably, the broader socioeconomic benefits are likely not being fully captured by the DALYs averted metric. No estimates of cost per DALY averted relating to community-wide mass antibiotic treatment for trachoma were found, highlighting the need for further research. These findings are important for informing global health policy and support the need for continuing NTD control and elimination efforts.

Lives saved with vaccination for 10 pathogens across 112 countries in a pre-COVID-19 world.

Background: Vaccination is one of the most effective public health interventions. We investigate the impact of vaccination activities for Haemophilus influenzae type b, hepatitis B, human papillomavirus, Japanese encephalitis, measles, Neisseria meningitidis serogroup A, rotavirus, rubella, Streptococcus pneumoniae, and yellow fever over the years 2000-2030 across 112 countries. Methods: Twenty-one mathematical models estimated disease burden using standardised demographic and immunisation data. Impact was attributed to the year of vaccination through vaccine-activity-stratified impact ratios. Results: We estimate 97 (95%CrI[80, 120]) million deaths would be averted due to vaccination activities over 2000-2030, with 50 (95%CrI[41, 62]) million deaths averted by activities between 2000 and 2019. For children under-5 born between 2000 and 2030, we estimate 52 (95%CrI[41, 69]) million more deaths would occur over their lifetimes without vaccination against these diseases. Conclusions: This study represents the largest assessment of vaccine impact before COVID-19-related disruptions and provides motivation for sustaining and improving global vaccination coverage in the future. Funding: VIMC is jointly funded by Gavi, the Vaccine Alliance, and the Bill and Melinda Gates Foundation (BMGF) (BMGF grant number: OPP1157270 / INV-009125). Funding from Gavi is channelled via VIMC to the Consortium's modelling groups (VIMC-funded institutions represented in this paper: Imperial College London, London School of Hygiene and Tropical Medicine, Oxford University Clinical Research Unit, Public Health England, Johns Hopkins University, The Pennsylvania State University, Center for Disease Analysis Foundation, Kaiser Permanente Washington, University of Cambridge, University of Notre Dame, Harvard University, Conservatoire National des Arts et Métiers, Emory University, National University of Singapore). Funding from BMGF was used for salaries of the Consortium secretariat (authors represented here: TBH, MJ, XL, SE-L, JT, KW, NMF, KAMG); and channelled via VIMC for travel and subsistence costs of all Consortium members (all authors). We also acknowledge funding from the UK Medical Research Council and Department for International Development, which supported aspects of VIMC's work (MRC grant number: MR/R015600/1).JHH acknowledges funding from National Science Foundation Graduate Research Fellowship; Richard and Peggy Notebaert Premier Fellowship from the University of Notre Dame. BAL acknowledges funding from NIH/NIGMS (grant number R01 GM124280) and NIH/NIAID (grant number R01 AI112970). The Lives Saved Tool (LiST) receives funding support from the Bill and Melinda Gates Foundation.This paper was compiled by all coauthors, including two coauthors from Gavi. Other funders had no role in study design, data collection, data analysis, data interpretation, or writing of the report. All authors had full access to all the data in the study and had final responsibility for the decision to submit for publication.

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'.

Strengthening data collection for neglected tropical diseases: What data are needed for models to better inform tailored intervention programmes?

Locally tailored interventions for neglected tropical diseases (NTDs) are becoming increasingly important for ensuring that the World Health Organization (WHO) goals for control and elimination are reached. Mathematical models, such as those developed by the NTD Modelling Consortium, are able to offer recommendations on interventions but remain constrained by the data currently available. Data collection for NTDs needs to be strengthened as better data are required to indirectly inform transmission in an area. Addressing specific data needs will improve our modelling recommendations, enabling more accurate tailoring of interventions and assessment of their progress. In this collection, we discuss the data needs for several NTDs, specifically gambiense human African trypanosomiasis, lymphatic filariasis, onchocerciasis, schistosomiasis, soil-transmitted helminths (STH), trachoma, and visceral leishmaniasis. Similarities in the data needs for these NTDs highlight the potential for integration across these diseases and where possible, a wider spectrum of diseases.

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.

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.

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.

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.