{"paper_id":"11fcef22-540b-419b-bf76-9ca36d7cdcf0","body_text":"Reaching Elimination of Onchocerciasis Transmission with Long-term Vector Control and Ivermectin Treatment in West Africa: The Example of Togo | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Reaching Elimination of Onchocerciasis Transmission with Long-term Vector Control and Ivermectin Treatment in West Africa: The Example of Togo Maria-Gloria Basanez, Luis Amaral, Rachel Bronzan, Anders Seim, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6284820/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 19 Dec, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Abstract The Onchocerciasis Control Programme in West Africa implemented vector control (VC) and ivermectin mass drug administration (MDA) to eliminate blindness. In Special Intervention Zones (SIZ), efforts were intensified. Togo aims to eliminate onchocerciasis transmission (EOT) by 2030. The stochastic EPIONCHO-IBM transmission model was used to project Onchocerca volvulus microfilarial prevalence trends in Togo’s five regions according to SIZ status, treatment coverage (65%-80% of total population) and VC efficacy (60%-100%). Model outputs were compared with microfilarial prevalence surveys (1970–2017, 400 villages) following four endemicity (baseline microfilarial prevalence) levels: hypoendemic (30%), mesoendemic (50%), hyperendemic (70%), and holoendemic (90%). EOT probabilities were calculated for 2024, 2027 and 2030. VC plus MDA substantially reduced prevalence. In holoendemic areas, this decline was not sustained after VC cessation despite biannual MDA. Baseline hypo- and mesoendemic areas can proceed with stop-MDA surveys (already underway). Highly endemic river basins would benefit from alternative treatment strategies (ATS). EPIONCHO-IBM captured Togo’s onchocerciasis trends throughout five decades of intervention. While most areas of the country may no longer require MDA, some are unlikely to reach EOT with current intervention strategies, indicating the need for ATS. Our modelling approach could be used in other endemic countries to inform policy decisions towards the 2030 elimination goals. Health sciences/Diseases/Infectious diseases/Parasitic infection Biological sciences/Computational biology and bioinformatics/Computational models onchocerciasis vector control ivermectin elimination modelling Togo Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 INTRODUCTION Onchocerciasis, caused by the filarial nematode Onchocerca volvulus and transmitted by Simulium blackflies, remains a public health concern, particularly in sub-Saharan Africa where mean microfilarial prevalence in 2018 exceeded 25% in some countries [1]. The Global Burden of Disease 2021 Study estimated 1.3 (0.8-1.9) million disability-adjusted life-years, and 20 (18-22) million people infected [2]. Ocular, cutaneous and neuro-hormonal sequelae cause substantial morbidity [3,4] and excess mortality [5]. Interventions include vector control (VC) and mass drug administration (MDA) of ivermectin for prolonged periods, owing to the 10-year (average) adult worm lifespan [6]. The Onchocerciasis Control Programme in West Africa (OCP, 1974-2002) aimed to eliminate onchocercal blindness through weekly aerial larviciding of Simulium damnosum sensu lato (s.l.) riverine breeding sites for ≥14 years [7]. In the late 1980s, ivermectin MDA was introduced alongside VC or, in some Western Extension foci, as the sole intervention [8]. In 2012, the goal shifted from morbidity control to elimination of transmission (EOT) [9]. Achieving EOT with MDA largely depends on pre-control endemicity (baseline microfilarial prevalence), determined by vector biting rates [10]. The impact of MDA on transmission is influenced by therapeutic coverage (proportion of population receiving treatment) and adherence (proportion of eligibles consistently taking treatment). It has been proposed that a minimal therapeutic coverage of 65% of total population (80% of eligibles) should be reached and sustained for at least 15-17 years to achieve elimination goals [11,12]. The World Health Organization’s 2021-2030 Roadmap on neglected tropical diseases (NTDs) aims at verifying onchocerciasis EOT in 12 (31%) endemic countries by 2030 [13]. Verification of EOT requires stop-MDA surveys and, if successful, post-treatment surveillance (PTS) for 3-5 years following MDA cessation [11]. Togo, having eliminated four other NTDs [14], aims to achieve onchocerciasis EOT by 2030 [15]. The epidemiology of onchocerciasis is heterogeneous across its five regions, from north to south: Savanes, Kara, Centrale, Plateaux and Maritime (Figure 1, Supplementary Material 1 Text S1 (S1.1), Table S1, Figure S1), each further sub-divided into prefectures. The blackfly-prolific Oti River Basin and its tributaries (Kara, Kéran and Mô) (Figure 1), and at-risk hard-to-reach villages pose particular challenges to EOT [15,16]. Onchocerciasis control in Togo began with the OCP in the northwest, gradually expanding southward (Figure S2A, Table S2). Savanes, Kara and a portion of Centrale were included in the OCP early VC Phases II and III East (starting in 1976-77). The remaining areas of Centrale, Plateaux and Maritime, were covered by the Southern Extension (starting in 1988-89), and annual ivermectin MDA was introduced. By the end of the OCP in 2002, Kara and parts of Savanes and Centrale had not achieved satisfactory entomo-epidemiological results [17] and were included in the OCP Special Intervention Zones (SIZ, Figure S2B), receiving aerial larviciding until 2007 and intensified, biannual MDA until 2012 [18]. After the OCP/SIZ, Togo continued onchocerciasis control through annual or biannual MDA (Text S1, S1.2). Modelling studies and recent reviews suggest that EOT may be attainable in areas with low to moderate baseline endemicity through sustained, high-coverage annual MDA [19,20]. However, highly-endemic foci will likely require alternative treatment strategies (ATS), such as moxidectin MDA [19,21], potentially reinforced by community-directed \"slash-and-clear\" vector control [22]. Following 2015-2017 stop-MDA surveys in Maritime, similar surveys commenced in Savanes in 2023 [23]. To support evidence-based decision-making by the National Onchocerciasis Control Programme (NOCP), we modelled the temporal trends of O. volvulus microfilarial prevalence in Togo’s regions, comparing modelled projections with data from endemic villages surveyed over time. We calculated the likelihood of EOT for each prefecture to determine which areas can begin stop-MDA surveys or may require ATS. METHODS Prevalence data Cross-sectional surveys (1970-2017) provided microfilarial prevalence data for 400 endemic villages (Supplementary Material 1, Text S2, Table S1, Figures S3-S5). Villages were considered to have recorded baseline endemicity estimates if surveyed for O. volvulus microfilarial prevalence before the start of ivermectin MDA or <3 years after starting VC [7,24] ( n =148; 140 in OCP database). Other villages lacked baseline assessments ( n =252) but had surveys conducted after the start of interventions (Table S1). We used crude rather than age- and sex-standardised microfilarial prevalence because the latter was missing in 12% of the surveys, and there was a 0.99 Pearson’s correlation coefficient between crude and standardised prevalence (Figure S6) [24]. Wilson-score 95% confidence intervals (95%CIs) [25] were calculated for each prevalence estimate. Villages with baseline microfilarial prevalence (BMP) were categorised into four endemicity levels: hypoendemic (>0% but <40%), mesoendemic (≥40% but <60%), hyperendemic (≥60% but <80%) and holoendemic (≥80%) [20]. Four BMP values: 30%, 50%, 70% and 90% were modelled to capture these endemicity levels. For villages without recorded BMP, all four endemicity levels were simulated to identify their most likely initial endemicity category according to modelled microfilarial prevalence trajectories (Table S1). Baseline annual biting rates (ABRs, bites/person/year) were estimated by interpolating the relationship between microfilarial prevalence and ABR using the EPIONCHO-IBM transmission model [10], generating ABR=290 (for 30%), 615 (50%), 2,200 (70%), and 60,000 (90%) (Text S3, Tables S3-S4). EPIONCHO-IBM EPIONCHO-IBM is a stochastic, individual-based model simulating O. volvulus infection dynamics in a closed population (village) [10] (500 individuals for this work). It tracks the number of (male and female) adult worms and microfilarial load in each human host over time, and the mean number of infective, L3 larvae per blackfly vector. Adult worm and microfilarial mortality rates are parasite-age dependent, and adult female worm fecundity decreases with worm age [10]. Human exposure is age- and sex-dependent [26], and overdispersed among individuals following a gamma distribution with shape and rate parameter k E (=0.3 for this work) [10]. Parasite population abundance is regulated by density-dependent processes within humans and vectors [27], which contribute to endemic stability and intervention resilience [10,28]. A description of the model is provided in [10] (code available at: https://github.com/mrc-ide/EPIONCHO.IBM). Modelling interventions and scenarios EPIONCHO-IBM was implemented across the four endemicity levels aforementioned within Togo’s five regions, considering their SIZ status and intervention history (Table 1). Modelled interventions comprised VC and ivermectin MDA. Ivermectin MDA was modelled by incorporating microfilaricidal and embryostatic effects [29], and a permanent sterilising effect on adult female worms [30]. Therapeutic coverage (proportion of individuals receiving ivermectin at each round in the total population) was simulated as the mean treatment probability in any treatment round. A fixed proportion of systematic non-adherence (SNA) was used to represent eligible individuals never receiving treatment [10]. VC was simulated by reducing ABR based on assumed efficacy for the entire larviciding duration. ABR values were assumed to return to initial levels one year after VC cessation [31]. Three intervention scenarios were modelled: “minimal”, “reference” and “enhanced” (Table 2, Text S4). An additional scenario for Savanes was simulated with 100% VC efficacy [32], varying therapeutic coverage and SNA as per the three main scenarios. Biannual MDA started in 2003 or 2014 in some regions (Table 1). In 2020, MDA was modelled annually nationally due to the COVID-19 pandemic [33]. Microfilarial prevalence trends were simulated until 2030, with the last (annual or biannual) treatment in 2029. Text S5 (Figure S7) presents the proportion of the population surveyed over time. We followed the five principles of the NTD Modelling Consortium regarding Policy-Relevant Items for Reporting Models in Epidemiology of NTDs (PRIME-NTD) [34] (Text S6, Table S5). Table 1 . Simulated duration of aerial vector control (VC) and ivermectin mass drug administration (MDA) in Togo regions Intervention Region and Special Intervention Zone (SIZ) status Savanes Kara Centrale Plateaux Maritime SIZ Non-SIZ SIZ SIZ Non-SIZ non-SIZ non-SIZ Start of VC 1977 a 1977 a 1977 a 1977 1989 1989 1988 End of VC 1993 1993 2007 2007 2002 2002 2002 Simulated duration of VC 16 yr 16 yr 30 yr 30 yr 13 yr 13 yr 13 yr Start of annual MDA b 1991 Start of biannual MDA c 2003 NA 2003 2003 NA NA or 2014 d NA Simulated end of MDA e 2024, 2027 or 2030 2014 or 2020 f Simulated duration of MDA f 12 yr annual; 21, 24 or 27 yr biannual 33, 36 or 39 yr annual 12 yr annual; 21, 24 or 27 yr biannual 12 yr annual; 21, 24 or 27 yr biannual 33, 36 or 39 yr annual 33, 36 or 39 yr annual, or 23 yr annual and 10, 13 or 16 yr biannual 23 or 29 yr annual a VC may have started in 1976 in some river basins [24,35]. b According to the data and literature, ivermectin MDA started earlier (1988–1990) in parts of Savanes and Kara (e.g., Bassar, Doufelgou, Kéran and Kozah prefectures) [35,36], but with poor coverage [37]. Some prefectures initiated MDA later (1992-1995). As most prefectures started MDA in 1991, this year was taken for the start of MDA in all simulations. NA = Not applicable (biannual MDA not implemented). Supplementary Material 1, Table S2 presents prefecture-specific intervention details. c In 2020, annual rather than biannual MDA was modelled in all prefectures across Togo due to the COVID-19 pandemic [33]. d In Plateaux four prefectures were switched to biannual MDA in 2014 because microfilarial prevalence in some villages was ≥5% [38]. e For the visualisation of infection trends, microfilarial prevalence dynamics were modelled until 2030, with the last simulated treatment round taking place in 2029. For the calculation of elimination of transmission (EOT) probabilities, ivermectin MDA was modelled to stop in 2024, 2027 or 2030. f In Maritime, stop-MDA assessments were conducted in 2014-2017, indicating that it was possible to stop treatment in two prefectures. Subsequent stop-MDA assessments were performed in 2020-2023, showing that four prefectures were ready to stop treatment [39]. Table 2 . Vector control (VC) efficacy, therapeutic coverage (of total population) and proportion of systematic non-adherence (SNA) for ivermectin mass drug administration (MDA) for the three intervention scenarios simulated for Togo Scenario VC efficacy a Ivermectin MDA therapeutic coverage SNA 1991 – 1995 1996 – 2001 2002 – 2030 Minimal (upper uncertainty bound) 60% 50% 65% 65% 5.0% Reference (average) 75% 50% 65% 75% 2.5% Enhanced (lower uncertainty bound) 90% 65% 75% 80% 1.0% a For Savanes, 100% VC efficacy simulations were also run for the three scenarios [32]. See Supplementary Material 1, Text S4 for further details, and Supplementary Material 2 for reported coverage of total population. A total of 100 model repeats were run for each of the three intervention scenarios, four endemicity levels, five regions and SIZ status. The mean of the 100 runs yielded mean microfilarial prevalence dynamics over time. Prevalence trends were visualized using the “minimal” and “enhanced” scenarios as the upper and lower uncertainty bounds, with “reference” scenario representing the average. Simulated trends are presented alongside survey prevalence estimates with 95%CIs per region and SIZ status to illustrate infection trends and compare model outputs with observations. The proportion of the population examined for O. volvulus skin microfilariae decreased from >80% at the beginning of the OCP to <70% between 2006 and 2015 (Text S5, Figure S7). Table S6 lists the villages with recorded BMP. Infection trends of villages lacking BMP were visually compared to model outputs for all endemicity settings and intervention scenarios to infer their most likely initial endemicity level (Text S7). Elimination probabilities For simulation of EOT probabilities, MDA frequencies from 2018 (annual or biannual, depending on prefecture) were used. The probability of reaching EOT for each scenario, region and SIZ status was calculated as the percentage of 100 model runs yielding zero microfilarial prevalence 50 years after stopping MDA in 2024, 2027 or 2030 [40]. For Maritime, where MDA ended in some prefectures in 2014 and in all by 2020, simulations ceasing MDA in 2014 or 2020 were performed (Tables 1, S2). Five EOT probability categories were defined: <5%, 6-19%, 20-59%, 60-89% and ≥90%. Villages with projected EOT probabilities <90% if MDA stops in 2027 were listed (Supplementary Material 2, Text S8). Prefecture-wide likelihoods of reaching EOT were calculated (Text S9). RESULTS Prevalence trends by region Figures 2-6 present modelling results for the 140 OCP villages with recorded BMP estimates. Supplementary Material 1, Figures S8-S14 present results for villages without BMP estimates. Savanes Villages with BMP estimates in Savanes prefectures were hypo- to mesoendemic in SIZ and meso- to hyperendemic in non-SIZ areas (Figure 2). Prevalence decline was primarily driven by VC with enhanced (90%) or 100% efficacy (Figures 2A-2E), eventually leading to ≥90% EOT probability following initiation of MDA in hypo- to mesoendemic areas (Supplementary Material 2, Table S7). Some SIZ villages lacking recorded BMP (Oti River Basin) had high prevalence, following hyper- to holoendemic simulation trends (Figure S8). Kara Villages in Kara (all prefectures in SIZ) with recorded BMP estimates encompassed all endemicity levels (Figure 3). The intervention scenarios best capturing infection trends were: minimal for hypoendemicity (Figure 3A), reference for mesoendemicity (Figure 3B), and minimal (Mô River Basin), reference (Kara River Basin) or enhanced (Kara River Basin) for hyperendemicity (Figure 3C). Holoendemic villages aligned with the enhanced (Kéran River Basin) intervention scenario (Figure 4D), with the model capturing the observed prevalence rebound after VC cessation. Two-fifths (30/74) of villages without BMP estimates followed hyper- to holoendemicity trends (Figure S10). Centrale Villages with recorded BMP in Centrale were hyperendemic in SIZ and ranged from hypo- to hyperendemic in non-SIZ areas. The SIZ hyperendemic villages (Mô River Basin) aligned closely with the reference intervention scenario (Figure 4A). Model projections for non-SIZ hypo- and mesoendemic villages (Figures 4B-4C) suggested a similar impact across intervention scenarios, likely because VC and MDA started roughly at the same time, reducing variability. Non-SIZ hyperendemic villages (Mono River Basin) followed the enhanced intervention scenario (Figure 4D). Villages without recorded BMP ranged from hypo- to holoendemic (Figures S11-S12). Nearly all SIZ villages (13/14) lacking BMP followed hyper- to holoendemic trends (Mô River Basin) (Figure S11). Plateaux Villages in Plateux (all non-SIZ) with recorded BMP were evenly distributed among hypo-, meso- and hyperendemicity (Figure 5). Model outputs were similar for hypo- and mesoendemicity, as in Centrale (Figures 5A-5D). Prevalence trends in hyperendemic villages were mostly captured by the enhanced intervention scenario, with some following the minimal and reference scenarios (Figures 5E-5F, Mono River Basin). Several villages without BMP estimates followed hyperendemic trends (Figure S13). Prefectures continued with annual MDA or switched to biannual MDA in 2014 (Table S2). Maritime Villages in Maritime with recorded BMP were predominantly hypoendemic, and their modelled prevalence trends followed the reference and enhanced intervention scenarios (Figure 6A). The hyperendemic village depicted in Figure 6B was consistent with the enhanced scenario. Villages without BMP estimates generally exhibited low endemicity, except in Yoto and possibly Avé prefectures, where some trends suggested hyperendemicity following the enhanced intervention scenario (Figure S14). Elimination probabilities Supplementary Material 2, Tables S7-S12 present EOT probabilities per region, baseline endemicity, SIZ status and intervention scenario. In Savanes, all SIZ hypo- to (100% VC efficacy) hyperendemic villages and nearly all (86%) non-SIZ villages are projected to have reached ≥90% EOT probability by 2024. However, in the northwestern part of Savanes non-SIZ, surveys conducted in early to mid-1970s (not in the OCP database), indicated baseline hyperendemicity (Figure S1). As non-SIZ areas of Savanes did not receive biannual MDA and VC ceased in 1993 (Table 1), the projected EOT probabilities are <5%. SIZ villages without BMP estimates following hyperendemic trends are projected to have <90% probability of reaching EOT by 2024. Extending biannual MDA to 2027 or 2030 in putative hyperendemic villages does not improve their EOT probabilities, remaining at <5%, 20-59%, and 60-89%, under minimal, reference, and enhanced interventions, respectively (Table S7). In Kara and Centrale, most hypo- and mesoendemic villages (regardless of SIZ status and intervention scenario) are projected to have reached ≥90% EOT probability by 2024. Some non-SIZ mesoendemic villages of Centrale following the minimal scenario and annual MDA would only reach 60-89% EOT probability, even with MDA extended to 2030. Hyperendemic villages following the enhanced scenario are projected to have reached ≥90% EOT probability by 2024. By contrast, those following the minimal or reference scenarios would have 5-19% or 60-89% EOT probability by 2024, respectively. If treatment continues until 2030, the former’s EOT probability would increase to 20-59%. As in Savanes, holoendemic villages have <5% EOT probability (Tables S8-S9). In Plateaux, owing to its lower BMP compared to Kara and Centrale, VC started later and not all prefectures adopted biannual MDA. Hypoendemic villages (irrespective of treatment frequency) and mesoendemic villages following reference and enhanced scenarios with annual or biannual MDA, are projected to have reached ≥90% EOT probability by 2024. The same applies to mesoendemic villages following the minimal scenario under biannual MDA. Mesoendemic villages following the minimal scenario and hyperendemic villages following the enhanced scenario under annual MDA, would have had 60-89% EOT probability by 2024. Hyperendemic villages following minimal and reference scenarios under annual MDA would only reach <5% EOT probability by 2024 or 2030. Those following minimal and reference scenarios under biannual MDA would have reached, respectively, <5% and 5-19% EOT by 2024, with the latter increasing to 20-59% if biannual MDA were extended until 2030. By contrast, hyperendemic villages following the enhanced scenario and already under biannual MDA could reach ≥90% EOT if biannual treatment continues until 2030 (Table S10). In Maritime, only annual MDA had been implemented by 2018. Being the least endemic region, all hypoendemic villages, and those mesoendemic villages following the reference and enhanced scenarios, are projected to have reached ≥90% EOT probability regardless of whether treatment ceased in 2014 or 2020. However, in one confirmed (with) and several putative (without BMP) hyperendemic villages, the EOT probability is 20-59% in 2020. Extending treatment in such villages to 2024 or 2030 would increase it to 60-89% (Tables S11-S12). Supplementary Material 2, Tables S13-S24 list villages by region, SIZ status, and river basin for which EPIONCHO-IBM projects EOT probabilities <90% if MDA stops in 2027. Tables S25-S29 present the rationale and calculations of prefecture-wide likelihoods (joint probabilities) of achieving EOT. Figure 7 illustrates the (categorical) likelihood of reaching EOT if ivermectin MDA stops in 2027. DISCUSSION Modelling analyses of detailed spatiotemporal O. volvulus prevalence data from the OCP and other sources (Text S2) provided a unique opportunity to quantify the combined impact of VC and ivermectin MDA in a former OCP country. The epidemiology of onchocerciasis in Togo has changed profoundly over nearly 50 years of intervention, with some prefectures on the verge of reaching EOT (Fig. 7 ) and others projected not to reach EOT with current strategies. Our results illustrate the power of mathematical modelling in evaluating past, current and future epidemiology of onchocerciasis, to assist programmes in decision-making and resource allocation to maximise their chances of reaching the 2030 elimination goals. We identified regional epidemiological patterns, long-term prevalence declines, and subsequent increases in some cases. In Savanes non-SIZ, (hypo- to hyperendemic) villages with 90–100% VC efficacy had reached a very low microfilarial prevalence by the time MDA started (Figs. 2 and S8). This contrasts with other regions where VC was likely less impactful, underscoring the need for combining VC and MDA. After VC cessation, hypo- to mesoendemic villages performed well under MDA. Annual MDA sustained previous gains in hyperendemic villages, but only biannual MDA led to further prevalence declines (Figs. 4 – 5 , S10-S12). Holoendemic villages experienced prevalence increases after VC cessation, in both data and model outputs, even with biannual MDA (Figs. 4 , S9-S10). According to EPIONCHO-IBM, achieving ≥ 90% EOT probability by 2024 in hypo- and mesoendemic areas nationwide seems feasible, and stop-MDA surveys could start if not already underway. Conversely, modelled prevalence in areas with hyper- and holoendemic villages, such as the Oti River Basin (Savanes), and the Kéran and Mô River Basins (Kara and Centrale), show a stable pseudo-equilibrium since 2007 (Figs. 2 A- 2 B, 3 C- 3 D, 4 A), and are unlikely to achieve EOT under the current (biannual) MDA strategy, even if continued until 2030 (Tables S7-S9). Infection prevalence of 0.1-1.0% in blackflies was found for these river basins (2015), and of 0.5–0.8% in Mô (2018–2019), indicating active transmission [ 35 , 41 ]. In non-SIZ (northwestern) Savanes, where VC started and ended early [ 15 ], surveyed villages (with or without BMP estimates) are scarce in our database (Figure S4). However, based on surveys indicating hyperendemicity in the 1970s (Figure S1 ), EOT likelihood in Tandjouaré and Tône prefectures is < 90% (Fig. 7 ). Stop-MDA surveys in 2022 indicated some villages of potential concern in these prefectures [ 42 ]. Whilst most of Maritime would likely have reached ≥ 90% EOT probability by 2020, some villages without BMP estimates, mostly in Yoto Prefecture, followed hyperendemic trends with moderate (60–89%) EOT probability. Active transmission was confirmed in Yoto during the 2020–2023 stop-MDA survey, prompting focal biannual MDA [ 39 ]. Limitations. Although baseline ABRs were reduced during VC by its assumed efficacy, they were modelled as bouncing back one year after VC cessation [ 31 ]. Deforestation, particularly in western Plateaux and southern Centrale [ 43 ], may have led to secular changes in vector density [ 44 ] not considered in the model. However, in the Mô River Basin, 2015–2019 ABRs were 12,000–16,000 bites/person/year [ 35 , 41 ]. Although we modelled information from 400 villages, there may be many others, certainly those with > 2,000 people, for which we have no epidemiological data as they were only incorporated into the NOCP in 2018 [ 23 ]. Because we may not have fully captured within-region heterogeneity, our prefecture-wide EOT likelihood must be interpreted with caution. Also, EPIONCHO-IBM models closed populations, not accounting for movement of people and/or flies between villages or cross-border migration that could jeopardise EOT by re-introduction of infection from less-well controlled areas [ 42 ]. CONCLUSION Togo has made considerable progress towards onchocerciasis EOT owing to VC and ivermectin MDA, switching to biannual frequency where necessary. However, areas with confirmed or putative high baseline endemicity pose challenges to achieving nation-wide EOT. EPIONCHO-IBM has proven its usefulness in interpreting epidemiological data, and supports decisions regarding stop-MDA surveys (e.g., in hypo- to mesoendemic areas with ≥15 years of high-coverage MDA and/or biannual treatment). In hyper- and holendemic areas with low EOT probabilities (e.g., in Kara and Centrale), the model suggests that ATS [21] should be considered. In particular, biannual moxidectin MDA supplemented, if feasible, by “slash-and-clear” VC would be beneficial [22,40]. EPIONCHO-IBM could be used in other former OCP countries to inform policy decisions towards the 2030 elimination goals. Declarations Competing interests. All authors declare no competing interests. Additional information Supplementary information File 1 and File 2. Open Access. For the purpose of open access, the authors have applied a Creative Commons Attribution (CC BY) licence to any author-accepted manuscript version arising from this submission. Author Contributions. Conceptualization: L.-J.A., M.-G.B. Data exploration: J.I.D H. Data Curation: J.-L.A. Formal analysis: L.-J.A. Investigation and methodology: L.-J.A., J.I.D.H., M.W., M.-G.B. Software: J I.D.H. Resources: R.N.B., A.S., M.-G.B. Visualization: L.-J.A., M.W., M.-G.B. Supervision: M.W., M.-G.B. Funding acquisition: M.-G.B. Project administration: R.N.B., M.-G.B. Writing – original draft: L.-J.A., M.-G.B. Writing – review and editing: L.-J.A., R.N.B., A.S., M.-D.M., K.P., I.G.T., S.A., M.D., P.G., J.I.D.H., M.W., M.-G.B. Acknowledgements. L.-J.A. was funded by La Caixa Foundation (grant B005782). M. W. and M.-G. B. acknowledge funding by the Bill & Melinda Gates Foundation through the NTD Modelling Consortium (grants OPP1184344 and INV-030046). M.-G.B. acknowledges funding from the MRC Centre for Global Infectious Disease Analysis (grant MR/X020258/1), funded by the UK Medical Research Council (MRC). This UK-funded award is carried out in the frame of the Global Health EDCTP3 Joint Undertaking. We would like to thank the people of Togo who, over many years, participated in the surveys analysed in this paper. Special thanks go to Dr Paul Cantey for his introduction to the Togo team, and to Prof. Robert Colebunders for his support. Dr Natalie Vinkeles Melchers provided useful advice on the assumptions used for the control interventions implemented in Togo that informed Table 1. We also acknowledge Dr Philip Milton for his guidance during the early stages of the work, and Mr Aditya Ramani for calculating the range of annual biting rates for the holoendemic settings presented in Supplementary Material 1. This paper is dedicated to the memory of Prof. Yao Kassankogno whose contribution to data availability was invaluable. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The corresponding authors had final responsibility for the decision to submit for publication. Data availability. The database containing the epidemiological data has been made publicly available by Vinkeles Melchers et al. [ 15 ]. All information used for the analyses is contained in this database [ 15 ], and the figures, tables, and Supplementary Material files of this paper. Code accessibility The EPIONCHO-IBM model code is available at: https://github.com/mrc-ide/EPIONCHO.IBM . 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Int J Infect Dis 2022 ; 116:302–5. Little MP, Breitling LP, Basáñez MG, Alley ES, Boatin BA. Association between microfilarial load and excess mortality in onchocerciasis: an epidemiological study. Lancet 2004; 363:1514–21. Plaisier AP, Alley ES, van Oortmarssen GJ, Boatin BA, Habbema JDF. Required duration of combined annual ivermectin treatment and vector control in the Onchocerciasis Control Programme in west Africa. Bull World Health Organ 1997; 75:237–45. Hougard JM, Alley ES, Yaméogo L, Dadzie KY, Boatin BA. Eliminating onchocerciasis after 14 years of vector control: a proved strategy. J Infect Dis 2001; 184:497-503. Boatin B. The Onchocerciasis Control Programme in West Africa (OCP). Ann Trop Med Parasitol 2008 ; 102(Suppl 1):13–7. World Health Organization. Accelerating work to overcome the global impact of neglected tropical diseases: a roadmap for Implementation. 2012 . Available at: https://www.who.int/publications/i/item/WHO-HTM-NTD-2012. Accessed 21 March 2025. Hamley JID, Milton P, Walker M, Basáñez MG. Modelling exposure heterogeneity and density dependence in onchocerciasis using a novel individual-based transmission model, EPIONCHO-IBM: Implications for elimination and data needs. PLoS Negl Trop Dis 2019 ; 13:e0007557. World Health Organization. Guidelines for stopping mass drug administration and verifying elimination of human onchocerciasis: criteria and procedures. 2016 . Available at: https://www.who.int/publications/i/item/9789241510011. Accessed 21 March 2025. Makenga Bof JC, Ntumba Tshitoka F, Muteba D, Mansiangi P, Coppieters Y. Review of the National Program for Onchocerciasis Control in the Democratic Republic of the Congo. Trop Med Infect Dis 2019; 4:92. World Health Organization. Ending the neglect to attain the Sustainable Development Goals: a road map for neglected tropical diseases 2021–2030. 2021 . Available at: https://www.who.int/publications/i/item/9789240010352. Accessed 21 March 2025. 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Community-directed vector control to supplement mass drug distribution for onchocerciasis elimination in the Madi mid-North focus of Northern Uganda. PLoS Negl Trop Dis. 2018; 12:e0006702. Health & Development International. Control of Neglected Tropical Diseases. Annual Work Plan (1 October 2017-30 August 2017) Togo, FY2018. End Neglected Tropical Diseases in Africa. 2017 . Available at:. http://web.archive.org/web/20230614035201/https://endinafrica.org/wp-content/uploads/2018/04/Togo-Work-Plan-FY2018-Final.pdf. Accessed 21 March 2025. O'Hanlon SJ, Slater HC, Cheke RA, et al. Model-based geostatistical mapping of the prevalence of Onchocerca volvulus in West Africa. PLoS Negl Trop Dis 2016; 10:e0004328. Brown LD, Cai TT, DasGupta A. Interval estimation for a binomial proportion. Stat Sci 2001; 16:101–33. Filipe JAN, Boussinesq M, Renz A, et al. Human infection patterns and heterogeneous exposure in river blindness. Proc Natl Acad Sci U S A 2005 ; 102:15265–70. Basáñez MG, Walker M, Turner HC, Coffeng LE, de Vlas SJ, Stolk WA. River blindness: mathematical models for control and elimination. Adv Parasitol 2016; 94:247–341. Hamley JID, Walker M, Coffeng LE, et al. Structural uncertainty in onchocerciasis transmission models influences the estimation of elimination thresholds and selection of age groups for seromonitoring. J Infect Dis 2020; 221(Suppl 5):S510–18. Basáñez MG, Pion SDS, Boakes E, Filipe JAN, Churcher TS, Boussinesq M. Effect of single-dose ivermectin on Onchocerca volvulus: A systematic review and meta-analysis. Lancet Infect Dis 2008 ; 8: 310–22. Plaisier AP, Alley ES, Boatin BA, et al. Irreversible effects of ivermectin on adult parasites in onchocerciasis patients in the Onchocerciasis Control Programme in West Africa. J Infect Dis 1995 ; 172: 204–10. Routledge I, Walker M, Cheke RA, et al. Modelling the impact of larviciding on the population dynamics and biting rates of Simulium damnosum (s.l.): Implications for vector control as a complementary strategy for onchocerciasis elimination in Africa. Parasit Vectors 2018; 11:316. Boatin B, Molyneux DH, Hougard JM, et al. Patterns of epidemiology and control of onchocerciasis in west Africa. J Helminthol 1997; 71:91–101. Act to End Neglected Tropical Diseases. West Program. Semi-Annual Report (April 1–September 30, 2021), FY2021. Available at: https://www.actntdswest.org/sites/default/files/inline-files/Act%20West%20FY%2021%20Semi%20Annual%20Report%20II.docx.pdf. Accessed 21 March 2025. Behrend MR, Basáñez MG, Hamley JID, et al. NTD Modelling Consortium. Modelling for policy: the five principles of the Neglected Tropical Diseases Modelling Consortium. PLoS Negl Trop Dis 2020; 14:e0008033. Komlan K, Vossberg PS, Gantin RG, et al. Onchocerca volvulus infection and serological prevalence, ocular onchocerciasis and parasite transmission in northern and central Togo after decades of Simulium damnosum s.l. vector control and mass drug administration of ivermectin. PLoS Negl Trop Dis 2018; 12:e0006312. World Health Organization, Onchocerciasis Control Programme in West Africa. Country-specific onchocerciasis control issues: Benin, Burkina Faso, Côte d'Ivoire, Ghana, Guinea, Guinea-Bissau, Mali, Niger, Sénégal, Sierra Leone, Togo. Ouagadougou 23-27 September 2002. Available at: https://iris.who.int/handle/10665/311573. Accessed 21 March 2025. World Health Organization, Onchocerciasis Control Programme in West Africa. Report of the evaluation of the ivermectin distribution in four countries: Côte d’Ivoire, Benin, Togo and Ghana. Ouagadougou 4 May 1996. Available at: https://iris.who.int/bitstream/handle/10665/339196/339196-eng.pdf?sequence=1&isAllowed=y. Accessed 21 March 2025. Health & Development International. Control of Neglected Tropical Diseases. Annual Work Plan (1 October 2015–30 September 2016) Togo, FY2016. Available at: http://web.archive.org/web/20230729131709/https://endinafrica.org/wp-content/uploads/2018/04/Togo-Work-Plan-FY2016.pdf. Accessed 21 March 2025. USAID, Act to End Neglected Tropical Diseases. West Program. Work plan Togo (October 1, 2022-September 30, 2023), FY2023. Available at: https://www.actntdswest.org/sites/default/files/inline-files/Act%20West%20FY23%20Workplan-Togo.pdf . Accessed 21 March 2025. Kura K, Milton P, Hamley JID, et al. Can mass drug administration of moxidectin accelerate onchocerciasis elimination in Africa? Philos Trans R Soc Lond B Biol Sci 2023; 378:20220277. Johanns SI, Gantin RG, Wangala B, et al. Onchocerca volvulus -specific antibody and cellular responses in onchocerciasis patients treated annually with ivermectin for 30 years and exposed to parasite transmission in central Togo. PLoS Negl Trop Dis 2022; 16:e0010340. World Health Organization, Global Onchocerciasis Network for Elimination. Summary of presentations and discussions of GONE webinar: Togo on its path towards the elimination of onchocerciasis (11 June 2024), 2024 . Available at: https://cdn.who.int/media/docs/default-source/ntds/onchocerciasis/global-onchocerciasis-network-for-elimination-(gone)/webinar-reports/gone-webinar-report-togo-jun-2024-eng-fr.pdf?sfvrsn=5e782f71_3&download=true. Accessed 21 March 2025. Global Forest Watch. Location of tree cover loss in Togo. Available at: https://www.globalforestwatch.org/dashboards/country/TGO/?category=forest-change&map=eyJjYW5Cb3VuZCI6dHJ1ZX0%3D. Accessed 21 March, 2025. Wilson MD, Cheke RA, Flasse SP, et al. Deforestation and the spatio-temporal distribution of savannah and forest members of the Simulium damnosum complex in southern Ghana and south-western Togo. Trans R Soc Trop Med Hyg 2002; 96:632–39. Additional Declarations There is NO Competing Interest. Supplementary Files Amaraletal.SIFile122.03.2025.pdf Supplementary Material 1 Amaraletal.SIFile222.03.2025.pdf Supplementary Material 2 Cite Share Download PDF Status: Published Journal Publication published 19 Dec, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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Togo regions are indicated by grey borders and names; main rivers are indicated by light blue and names. River basins with superscript 1 are named but not depicted. Mô is a tributary of the Oti River. Ogou and Amou are tributaries of the Mono River. Yoto and Haho flow towards the delta of the Maritime Region. Maps and shape files used are from Open Access sources compliant with Creative Commons Attribution (CC BY) licence.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage1.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6284820/v1/ab71f43fc610bd9acaf90ea6.jpeg\"},{\"id\":80020166,\"identity\":\"ecb88c3d-1737-42ca-bf21-8d92ea0a895b\",\"added_by\":\"auto\",\"created_at\":\"2025-04-07 04:39:39\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":185388,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cem\\u003eOnchocerca volvulus\\u003c/em\\u003emicrofilarial prevalence trends simulated using EPIONCHO-IBM (until 2030) for Savanes Region villages with recorded pre-control baseline microfilarial prevalence (BMP) estimates, vector control (VC) and ivermectin mass drug administration (MDA). For Special Intervention Zones (SIZ): \\u003cem\\u003eA\\u003c/em\\u003e, hypoendemic village (\\u003cem\\u003en\\u003c/em\\u003e=1) with simulated 30% BMP, 100% VC efficacy and biannual MDA. \\u003cem\\u003eB\\u003c/em\\u003e, mesoendemic village (\\u003cem\\u003en\\u003c/em\\u003e=1) with simulated 50% BMP and biannual MDA. \\u003cem\\u003eC\\u003c/em\\u003e, mesoendemic villages (\\u003cem\\u003en\\u003c/em\\u003e=2) with simulated 50% BMP, 100% VC efficacy and biannual MDA. For Non-Special Intervention Zones (non-SIZ): \\u003cem\\u003eD\\u003c/em\\u003e, mesoendemic village (\\u003cem\\u003en\\u003c/em\\u003e=1) with simulated 50% BMP; \\u003cem\\u003eE,\\u003c/em\\u003e hyperendemic villages (\\u003cem\\u003en\\u003c/em\\u003e=2) and 70% BMP with 100% VC efficacy. Yellow circles represent hypoendemic villages, orange circles indicate mesoendemic villages, and brown circles denote hyperendemic villages. Error bars are 95% (Wilson score) confidence intervals (95% CIs). For each BMP setting and intervention scenario, the average of 100 model repeats was used to calculate the mean microfilarial prevalence dynamics (blue lines). Dark blue lines represent the reference scenario; light blue lines above and below dark blue lines indicate the minimal and enhanced scenarios, respectively. Vertical coloured lines indicate: start of VC (light green); start of annual MDA (red); end of VC (dark green); start of biannual MDA (orange). Further information about the individual villages plotted here can be found in Supplementary Material 1, Table S6.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6284820/v1/07a07cda1ca5a68cf0a18182.png\"},{\"id\":80020168,\"identity\":\"db8feff7-ce91-4fdd-823b-7aab7df89281\",\"added_by\":\"auto\",\"created_at\":\"2025-04-07 04:39:39\",\"extension\":\"png\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":218167,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cem\\u003eOnchocerca volvulus\\u003c/em\\u003emicrofilarial prevalence trends simulated using EPIONCHO-IBM (until 2030) for Kara Region villages with recorded pre-control baseline microfilarial prevalence (BMP) estimates, vector control (VC) and ivermectin mass drug administration (MDA).\\u003cstrong\\u003e \\u003c/strong\\u003eFor Special Intervention Zones (SIZ, all villages): \\u003cem\\u003eA\\u003c/em\\u003e, hypoendemic villages (\\u003cem\\u003en\\u003c/em\\u003e=2) with simulated 30% BMP and biannual MDA. \\u003cem\\u003eB\\u003c/em\\u003e, mesoendemic villages (\\u003cem\\u003en\\u003c/em\\u003e=2) with simulated 50% BMP and biannual MDA. \\u003cem\\u003eC\\u003c/em\\u003e, hyperendemic villages (\\u003cem\\u003en\\u003c/em\\u003e=6) with simulated 70% BMP and biannual MDA. \\u003cem\\u003eD\\u003c/em\\u003e, holoendemic villages (\\u003cem\\u003en\\u003c/em\\u003e=2) with simulated 90% BMP and biannual MDA. Yellow circles represent hypoendemic villages, orange circles indicate mesoendemic villages, and brown circles denote hyper- and holoendemic villages. Error bars are 95% (Wilson score) confidence intervals (95% CIs). For each BMP setting and intervention scenario, the average of 100 model repeats was used to calculate the mean microfilarial prevalence dynamics (blue lines). Dark blue lines represent the reference scenario; light blue lines above and below dark blue lines indicate the minimal and enhanced scenarios, respectively. Vertical coloured lines indicate: start of VC (light green); start of annual MDA (red); end of VC (dark green); start of biannual MDA (orange). Further information about the individual villages plotted here can be found in Supplementary Material 1, Table S6.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6284820/v1/6b3ff858493127107a412f1f.png\"},{\"id\":80020367,\"identity\":\"995a6d4a-c91f-4c46-88fc-c36372ce3269\",\"added_by\":\"auto\",\"created_at\":\"2025-04-07 04:47:39\",\"extension\":\"png\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":184910,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cem\\u003eOnchocerca volvulus\\u003c/em\\u003emicrofilarial prevalence trends simulated using EPIONCHO-IBM (until 2030) for Centrale Region villages with recorded pre-control baseline microfilarial prevalence (BMP) estimates, vector control (VC) and ivermectin mass drug administration (MDA).\\u003cstrong\\u003e \\u003c/strong\\u003eFor Special Intervention Zones (SIZ): \\u003cem\\u003eA,\\u003c/em\\u003e hyperendemic villages (\\u003cem\\u003en\\u003c/em\\u003e=2) with 70% BMP and biannual MDA. For Non-Special Intervention Zones (non-SIZ): \\u003cem\\u003eB\\u003c/em\\u003e, hypoendemic villages (\\u003cem\\u003en\\u003c/em\\u003e=13) with 30% BMP. \\u003cem\\u003eC\\u003c/em\\u003e, mesoendemic villages (\\u003cem\\u003en\\u003c/em\\u003e=26) with 50% BMP. \\u003cem\\u003eD\\u003c/em\\u003e, hyperendemic villages (\\u003cem\\u003en\\u003c/em\\u003e=5) with 70% BMP. Yellow circles represent hypoendemic villages, orange circles indicate mesoendemic villages, and brown circles denote hyperendemic villages. Error bars are 95% (Wilson score) confidence intervals (95%CIs). For each BMP setting and intervention scenario, the average of 100 model repeats was used to calculate the mean microfilarial prevalence dynamics (blue lines). Dark blue lines represent the reference scenario; light blue lines above and below dark blue lines indicate the minimal and enhanced scenarios, respectively. Vertical coloured lines indicate: start of VC (light green); start of annual MDA (red); end of VC (dark green); start of biannual MDA (orange). Further information about the individual villages plotted here can be found in Supplementary Material 1, Table S6.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage4.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6284820/v1/3af1c7319217b1c5dcd1e661.png\"},{\"id\":80020170,\"identity\":\"99ce084e-4d14-4a5a-8cca-6ea6f7616c96\",\"added_by\":\"auto\",\"created_at\":\"2025-04-07 04:39:39\",\"extension\":\"png\",\"order_by\":5,\"title\":\"Figure 5\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":315168,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cem\\u003eOnchocerca volvulus\\u003c/em\\u003emicrofilarial prevalence trends simulated using EPIONCHO-IBM (until 2030) for Plateaux Region villages (all non-Special Intervention Zones) with recorded pre-control baseline microfilarial prevalence (BMP) estimates, vector control (VC) and ivermectin mass drug administration (MDA). \\u003cem\\u003eA\\u003c/em\\u003e, hypoendemic villages (\\u003cem\\u003en\\u003c/em\\u003e=12) with simulated 30% BMP and annual MDA. \\u003cem\\u003eB\\u003c/em\\u003e, hypoendemic villages (\\u003cem\\u003en\\u003c/em\\u003e=4) with 30% BMP and biannual MDA. \\u003cem\\u003eC\\u003c/em\\u003e, mesoendemic villages (\\u003cem\\u003en\\u003c/em\\u003e=15) with 50% BMP and annual MDA. \\u003cem\\u003eD\\u003c/em\\u003e, mesoendemic villages (\\u003cem\\u003en\\u003c/em\\u003e=12) with 50% BMP and biannual MDA. \\u003cem\\u003eE\\u003c/em\\u003e, hyperendemic villages (\\u003cem\\u003en\\u003c/em\\u003e=12) with 70% BMP and annual MDA. \\u003cem\\u003eF\\u003c/em\\u003e, hyperendemic villages (\\u003cem\\u003en\\u003c/em\\u003e=13) with 70% BMP and biannual MDA. Yellow circles represent hypoendemic villages, orange circles indicate mesoendemic villages, and brown circles denote hyperendemic villages. Error bars are 95% (Wilson score) confidence intervals (95%CIs). For each BMP setting and intervention scenario, the average of 100 model repeats was used to calculate the mean microfilarial prevalence dynamics (blue lines). Dark blue lines represent the reference scenario; light blue lines above and below dark blue lines indicate the minimal and enhanced scenarios, respectively. Vertical coloured lines indicate: start of VC (light green); start of annual MDA (red); end of VC (dark green); start of biannual MDA (orange). Further information about individual villages plotted here can be found in Supplementary Material 1, Table S6.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage5.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6284820/v1/b4744b47c70b5e23ed027e6a.png\"},{\"id\":80020172,\"identity\":\"86fd3a16-8adf-4499-b0fd-62c9d7154ba1\",\"added_by\":\"auto\",\"created_at\":\"2025-04-07 04:39:39\",\"extension\":\"png\",\"order_by\":6,\"title\":\"Figure 6\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":90039,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cem\\u003eOnchocerca volvulus\\u003c/em\\u003emicrofilarial prevalence trends simulated using EPIONCHO-IBM (until 2030) for Maritime Region villages (all non-Special Intervention Zones) with recorded pre-control baseline microfilarial prevalence (BMP) estimates, vector control (VC) and ivermectin mass drug administration (MDA). \\u003cem\\u003eA\\u003c/em\\u003e, hypoendemic villages (\\u003cem\\u003en\\u003c/em\\u003e=6) with simulated 30% BMP. \\u003cem\\u003eB\\u003c/em\\u003e, hyperendemic village (\\u003cem\\u003en\\u003c/em\\u003e=1) with 70% BMP. Yellow circles represent hypoendemic villages, and brown circles denote a hyperendemic village. Error bars are 95% (Wilson score) confidence intervals (95%CIs). For each BMP setting and intervention scenario, the average of 100 model repeats was used to calculate the mean microfilarial prevalence dynamics (blue lines). Dark blue lines represent the reference scenario; light blue lines above and below dark blue lines indicate the minimal and enhanced scenarios, respectively. Vertical coloured lines indicate: start of VC (light green); start of annual MDA (red); end of VC (dark green). Further information about the individual villagesplotted here can be found in Supplementary Material 1, Table S6.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage6.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6284820/v1/d0f99a66ddd8eb0578e7575d.png\"},{\"id\":80020370,\"identity\":\"53744637-8717-4058-8e24-8ee58e3944dd\",\"added_by\":\"auto\",\"created_at\":\"2025-04-07 04:47:39\",\"extension\":\"png\",\"order_by\":7,\"title\":\"Figure 7\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":253664,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eCategorical likelihood of elimination of onchocerciasis transmission (EOT) in Togo’s prefectures if ivermectin mass drug administration were stopped in 2027, according to EPIONCHO-IBM projections. Details of the calculation of the prefecture-wide (joint) EOT probabilities are given in Supplementary Material 2, Text S9. Categories are defined as: Very likely (≥90%); Likely (50-89%); Possibly (5-49%); Unlikely (0.01-\\u0026lt;5%), and Very unlikely (\\u0026lt;0.01%). The pie-charts indicate the proportion of the total number of villages surveyed in each prefecture that are projected to reach \\u0026lt;5%, 5-19%, 20-59%, 60-89% or ≥90% EOT probability, with the size of the pie-charts reflecting the number of villages (exact numbers are given in Table S28; detailed information on those villages with projected EOT probability \\u0026lt;90% is presented in Tables S13-S24). Black borders indicate regions (see Fig. 1); white borders correspond to prefectures. The map for Togo (with regions and prefectures) was drawn using the R package geodata version 0.6-2 (https://github.com/rspatial/geodata).\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage7.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6284820/v1/ecc7ab8a790087409811a42d.png\"},{\"id\":100949588,\"identity\":\"fd9e187d-274b-4eff-8153-5d6ef1fad5f6\",\"added_by\":\"auto\",\"created_at\":\"2026-01-23 07:04:32\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":2560873,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6284820/v1/32cbcbbe-0573-4537-a412-2a2f27ec20fd.pdf\"},{\"id\":80020369,\"identity\":\"caeec2e3-275b-4f59-845a-ec21fa8e0957\",\"added_by\":\"auto\",\"created_at\":\"2025-04-07 04:47:39\",\"extension\":\"pdf\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":2799188,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eSupplementary Material 1\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Amaraletal.SIFile122.03.2025.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6284820/v1/79611d27889dbcea693b9bb8.pdf\"},{\"id\":80020376,\"identity\":\"abd587bd-7b8c-4956-8ae0-67a89bc929ca\",\"added_by\":\"auto\",\"created_at\":\"2025-04-07 04:47:41\",\"extension\":\"pdf\",\"order_by\":2,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":1442066,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eSupplementary Material 2\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Amaraletal.SIFile222.03.2025.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6284820/v1/812405c2d56f2938b399f7a5.pdf\"}],\"financialInterests\":\"There is \\u003cb\\u003eNO\\u003c/b\\u003e Competing Interest.\",\"formattedTitle\":\"Reaching Elimination of Onchocerciasis Transmission with Long-term Vector Control and Ivermectin Treatment in West Africa: The Example of Togo\",\"fulltext\":[{\"header\":\"INTRODUCTION\",\"content\":\"\\u003cp\\u003eOnchocerciasis, caused by the filarial nematode \\u003cem\\u003eOnchocerca volvulus\\u003c/em\\u003e and transmitted by \\u003cem\\u003eSimulium\\u003c/em\\u003e blackflies, remains a public health concern, particularly in sub-Saharan Africa where mean microfilarial prevalence in 2018 exceeded 25% in some countries [1]. The Global Burden of Disease 2021 Study estimated 1.3 (0.8-1.9) million disability-adjusted life-years, and 20 (18-22) million people infected [2]. Ocular, cutaneous and neuro-hormonal sequelae cause substantial morbidity [3,4] and excess mortality [5]. Interventions include vector control (VC) and mass drug administration (MDA) of ivermectin for prolonged periods, owing to the 10-year (average) adult worm lifespan [6].\\u003c/p\\u003e\\n\\u003cp\\u003eThe Onchocerciasis Control Programme in West Africa (OCP, 1974-2002) aimed to eliminate onchocercal blindness through weekly aerial larviciding of \\u003cem\\u003eSimulium damnosum sensu lato\\u003c/em\\u003e (s.l.) riverine breeding sites for \\u0026ge;14 years [7]. In the late 1980s, ivermectin MDA was introduced alongside VC or, in some Western Extension foci, as the sole intervention [8]. In 2012, the goal shifted from morbidity control to elimination of transmission (EOT) [9].\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eAchieving EOT with MDA largely depends on pre-control endemicity (baseline microfilarial prevalence), determined by vector biting rates [10]. The impact of MDA on transmission is influenced by therapeutic coverage (proportion of population receiving treatment) and adherence (proportion of eligibles consistently taking treatment). It has been proposed that a minimal therapeutic coverage of 65% of total population (80% of eligibles) should be reached and sustained for at least 15-17 years to achieve elimination goals [11,12].\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eThe World Health Organization\\u0026rsquo;s 2021-2030 Roadmap on neglected tropical diseases (NTDs) aims at verifying onchocerciasis EOT in 12 (31%) endemic countries by 2030 [13]. Verification of EOT requires stop-MDA surveys and, if successful, post-treatment surveillance (PTS) for 3-5 years following MDA cessation [11]. Togo, having eliminated four other NTDs [14], aims to achieve onchocerciasis EOT by 2030 [15]. The epidemiology of onchocerciasis is heterogeneous across its five regions, from north to south: Savanes, Kara, Centrale, Plateaux and Maritime (Figure 1, Supplementary Material 1 Text S1 (S1.1), Table S1, Figure S1), each further sub-divided into prefectures. The blackfly-prolific Oti River Basin and its tributaries (Kara, K\\u0026eacute;ran and M\\u0026ocirc;) (Figure 1), and at-risk hard-to-reach villages pose particular challenges to EOT [15,16].\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eOnchocerciasis control in Togo began with the OCP in the northwest, gradually expanding southward (Figure S2A, Table S2). Savanes, Kara and a portion of Centrale were included in the OCP early VC Phases II and III East (starting in 1976-77). The remaining areas of Centrale, Plateaux and Maritime, were covered by the Southern Extension (starting in 1988-89), and annual ivermectin MDA was introduced. By the end of the OCP in 2002, Kara and parts of Savanes and Centrale had not achieved satisfactory entomo-epidemiological results [17] and were included in the OCP Special Intervention Zones (SIZ, Figure S2B), receiving aerial larviciding until 2007 and intensified, biannual MDA until 2012 [18]. After the OCP/SIZ, Togo continued onchocerciasis control through annual or biannual MDA (Text S1, S1.2).\\u003c/p\\u003e\\n\\u003cp\\u003eModelling studies and recent reviews suggest that EOT may be attainable in areas with low to moderate baseline endemicity through sustained, high-coverage annual MDA [19,20]. However, highly-endemic foci will likely require alternative treatment strategies (ATS), such as moxidectin MDA [19,21], potentially reinforced by community-directed \\u0026quot;slash-and-clear\\u0026quot; vector control [22].\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eFollowing 2015-2017 stop-MDA surveys in Maritime, similar surveys commenced in Savanes in 2023 [23].\\u0026nbsp;To support evidence-based decision-making by the\\u0026nbsp;National Onchocerciasis Control Programme (NOCP), we modelled the temporal trends of \\u003cem\\u003eO.\\u0026nbsp;volvulus\\u003c/em\\u003e microfilarial prevalence in Togo\\u0026rsquo;s regions, comparing modelled projections with data from endemic villages surveyed over time. We calculated the likelihood of EOT for each prefecture to determine which areas can begin stop-MDA surveys or may require ATS.\\u003c/p\\u003e\"},{\"header\":\"METHODS\",\"content\":\"\\u003ch2\\u003ePrevalence data\\u003c/h2\\u003e\\n\\u003cp\\u003eCross-sectional surveys (1970-2017) provided microfilarial prevalence data for 400 endemic villages (Supplementary Material 1, Text S2, Table S1, Figures S3-S5). Villages were considered to have recorded baseline endemicity estimates if surveyed for \\u003cem\\u003eO. volvulus\\u003c/em\\u003e microfilarial prevalence before the start of ivermectin MDA or \\u0026lt;3 years after starting VC [7,24] (\\u003cem\\u003en\\u003c/em\\u003e=148; 140 in OCP database). Other villages lacked baseline assessments (\\u003cem\\u003en\\u003c/em\\u003e=252) but had surveys conducted after the start of interventions (Table S1). We used crude rather than age- and sex-standardised microfilarial prevalence because the latter was missing in 12% of the surveys, and there was a 0.99 Pearson\\u0026rsquo;s correlation coefficient between crude and standardised prevalence (Figure S6) [24]. Wilson-score 95% confidence intervals (95%CIs)\\u0026nbsp;[25]\\u0026nbsp;were calculated for each prevalence estimate.\\u003c/p\\u003e\\n\\u003cp\\u003eVillages with baseline microfilarial prevalence (BMP) were categorised into four endemicity levels: hypoendemic (\\u0026gt;0% but \\u0026lt;40%), mesoendemic (\\u0026ge;40% but \\u0026lt;60%), hyperendemic (\\u0026ge;60% but \\u0026lt;80%) and holoendemic (\\u0026ge;80%) [20]. Four BMP values: 30%, 50%, 70% and 90% were modelled to capture these endemicity levels. For villages without recorded BMP, all four endemicity levels were simulated to identify their most likely initial endemicity category according to modelled microfilarial prevalence trajectories (Table S1). Baseline annual biting rates (ABRs, bites/person/year) were estimated by interpolating the relationship between microfilarial prevalence and ABR using the EPIONCHO-IBM transmission model [10], generating ABR=290 (for 30%), 615 (50%), 2,200 (70%), and 60,000 (90%) (Text S3, Tables S3-S4).\\u0026nbsp;\\u003c/p\\u003e\\n\\u003ch2\\u003eEPIONCHO-IBM\\u003c/h2\\u003e\\n\\u003cp\\u003eEPIONCHO-IBM is a stochastic, individual-based model simulating \\u003cem\\u003eO. volvulus\\u003c/em\\u003e infection dynamics in a closed population (village) [10] (500 individuals for this work). It tracks the number of (male and female) adult worms and microfilarial load in each human host over time, and the mean number of infective, L3 larvae per blackfly vector. Adult worm and microfilarial mortality rates are parasite-age dependent, and adult female worm fecundity decreases with worm age [10]. Human exposure is age- and sex-dependent [26], and overdispersed among individuals following a gamma distribution with shape and rate parameter \\u003cem\\u003ek\\u003c/em\\u003e\\u003csub\\u003eE\\u003c/sub\\u003e (=0.3 for this work) [10]. Parasite population abundance is regulated by density-dependent processes within humans and vectors [27], which contribute to endemic stability and intervention resilience [10,28]. A description of the model is provided in [10] (code available at: https://github.com/mrc-ide/EPIONCHO.IBM).\\u003c/p\\u003e\\n\\u003ch2\\u003eModelling interventions and scenarios\\u003c/h2\\u003e\\n\\u003cp\\u003eEPIONCHO-IBM was implemented across the four endemicity levels aforementioned within Togo\\u0026rsquo;s five regions, considering their SIZ status and intervention history (Table 1). Modelled interventions comprised VC and ivermectin MDA. Ivermectin MDA was modelled by incorporating microfilaricidal and embryostatic effects [29], and a permanent sterilising effect on adult female worms [30]. Therapeutic coverage (proportion of individuals receiving ivermectin at each round in the total population) was simulated as the mean treatment probability in any treatment round. A fixed proportion of systematic non-adherence (SNA) was used to represent eligible individuals never receiving treatment [10]. VC was simulated by reducing ABR based on assumed efficacy for the entire larviciding duration. ABR values were assumed to return to initial levels one year after VC cessation [31].\\u003c/p\\u003e\\n\\u003cp\\u003eThree intervention scenarios were modelled: \\u0026ldquo;minimal\\u0026rdquo;, \\u0026ldquo;reference\\u0026rdquo; and \\u0026ldquo;enhanced\\u0026rdquo; (Table 2, Text S4). An additional scenario for Savanes was simulated with 100% VC efficacy [32], varying therapeutic coverage and SNA as per the three main scenarios. Biannual MDA started in 2003 or 2014 in some regions (Table 1). In 2020, MDA was modelled annually nationally due to the COVID-19 pandemic [33]. Microfilarial prevalence trends were simulated until 2030, with the last (annual or biannual) treatment in 2029. Text S5 (Figure S7) presents the proportion of the population surveyed over time.\\u003c/p\\u003e\\n\\u003cp\\u003eWe followed the five principles of the NTD Modelling Consortium regarding Policy-Relevant Items for Reporting Models in Epidemiology of NTDs (PRIME-NTD) [34] (Text S6, Table S5).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eTable 1\\u003c/strong\\u003e\\u003cstrong\\u003e. Simulated duration of aerial vector control (VC) and ivermectin mass drug administration (MDA) in Togo regions\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003ctable border=\\\"1\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" width=\\\"964\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"3\\\" valign=\\\"top\\\" style=\\\"width: 180px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eIntervention\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"7\\\" valign=\\\"top\\\" style=\\\"width: 784px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eRegion and Special Intervention Zone (SIZ) status\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 217px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eSavanes\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 113px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eKara\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 208px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eCentrale\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 132px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePlateaux\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 113px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMaritime\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003eSIZ\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 113px;\\\"\\u003e\\n \\u003cp\\u003eNon-SIZ\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 113px;\\\"\\u003e\\n \\u003cp\\u003eSIZ\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003eSIZ\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003eNon-SIZ\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 132px;\\\"\\u003e\\n \\u003cp\\u003enon-SIZ\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 113px;\\\"\\u003e\\n \\u003cp\\u003enon-SIZ\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 180px;\\\"\\u003e\\n \\u003cp\\u003eStart of VC\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003e1977\\u003csup\\u003ea\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 113px;\\\"\\u003e\\n \\u003cp\\u003e1977\\u003csup\\u003ea\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 113px;\\\"\\u003e\\n \\u003cp\\u003e1977\\u003csup\\u003ea\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003e1977\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003e1989\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 132px;\\\"\\u003e\\n \\u003cp\\u003e1989\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 113px;\\\"\\u003e\\n \\u003cp\\u003e1988\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 180px;\\\"\\u003e\\n \\u003cp\\u003eEnd of VC\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003e1993\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 113px;\\\"\\u003e\\n \\u003cp\\u003e1993\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 113px;\\\"\\u003e\\n \\u003cp\\u003e2007\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003e2007\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003e2002\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 132px;\\\"\\u003e\\n \\u003cp\\u003e2002\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 113px;\\\"\\u003e\\n \\u003cp\\u003e2002\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 180px;\\\"\\u003e\\n \\u003cp\\u003eSimulated duration of VC\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003e16 yr\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 113px;\\\"\\u003e\\n \\u003cp\\u003e16 yr\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 113px;\\\"\\u003e\\n \\u003cp\\u003e30 yr\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003e30 yr\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003e13 yr\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 132px;\\\"\\u003e\\n \\u003cp\\u003e13 yr\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 113px;\\\"\\u003e\\n \\u003cp\\u003e13 yr\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 180px;\\\"\\u003e\\n \\u003cp\\u003eStart of annual MDA\\u003csup\\u003eb\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"7\\\" valign=\\\"top\\\" style=\\\"width: 784px;\\\"\\u003e\\n \\u003cp\\u003e1991\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 180px;\\\"\\u003e\\n \\u003cp\\u003eStart of biannual MDA\\u003csup\\u003ec\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003e2003\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 113px;\\\"\\u003e\\n \\u003cp\\u003eNA\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 113px;\\\"\\u003e\\n \\u003cp\\u003e2003\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003e2003\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003eNA\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 132px;\\\"\\u003e\\n \\u003cp\\u003eNA or 2014\\u003csup\\u003ed\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 113px;\\\"\\u003e\\n \\u003cp\\u003eNA\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 180px;\\\"\\u003e\\n \\u003cp\\u003eSimulated end of MDA\\u003csup\\u003ee\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"6\\\" valign=\\\"top\\\" style=\\\"width: 671px;\\\"\\u003e\\n \\u003cp\\u003e2024, 2027 or 2030\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 113px;\\\"\\u003e\\n \\u003cp\\u003e2014 or 2020\\u003csup\\u003ef\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 180px;\\\"\\u003e\\n \\u003cp\\u003eSimulated duration of MDA\\u003csup\\u003ef\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003e12 yr annual; 21, 24 or 27 yr biannual\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 113px;\\\"\\u003e\\n \\u003cp\\u003e33, 36 or 39 yr annual\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 113px;\\\"\\u003e\\n \\u003cp\\u003e12 yr annual; 21, 24 or 27 yr biannual\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003e12 yr annual; 21, 24 or 27 yr biannual\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003e33, 36 or 39 yr annual\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 132px;\\\"\\u003e\\n \\u003cp\\u003e33, 36 or 39 yr annual, or 23 yr annual and 10, 13 or 16 yr biannual\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 113px;\\\"\\u003e\\n \\u003cp\\u003e23 or 29 yr annual\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\\n\\u003cp\\u003e\\u003csup\\u003ea\\u003c/sup\\u003eVC may have started in 1976 in some river basins [24,35]. \\u003csup\\u003eb\\u003c/sup\\u003eAccording to the data and literature, ivermectin MDA started earlier (1988\\u0026ndash;1990) in parts of Savanes and Kara (e.g., Bassar, Doufelgou, K\\u0026eacute;ran and Kozah prefectures) [35,36], but with poor coverage [37]. Some prefectures initiated MDA later (1992-1995). As most prefectures started MDA in 1991, this year was taken for the start of MDA in all simulations. NA = Not applicable (biannual MDA not implemented). Supplementary Material 1, Table S2 presents prefecture-specific intervention details. \\u003csup\\u003ec\\u003c/sup\\u003eIn 2020, annual rather than biannual MDA was modelled in all prefectures across Togo due to the COVID-19 pandemic [33]. \\u003csup\\u003ed\\u003c/sup\\u003eIn Plateaux four prefectures were switched to biannual MDA in 2014 because microfilarial prevalence in some villages was \\u0026ge;5% [38]. \\u003csup\\u003ee\\u003c/sup\\u003eFor the visualisation of infection trends, microfilarial prevalence dynamics were modelled until 2030, with the last simulated treatment round taking place in 2029. For the calculation of elimination of transmission (EOT) probabilities, ivermectin MDA was modelled to stop in 2024, 2027 or 2030. \\u003csup\\u003ef\\u003c/sup\\u003eIn Maritime, stop-MDA assessments were conducted in 2014-2017, indicating that it was possible to stop treatment in two prefectures. Subsequent stop-MDA assessments were performed in 2020-2023, showing that four prefectures were ready to stop treatment [39].\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eTable 2\\u003c/strong\\u003e. \\u003cstrong\\u003eVector control (VC) efficacy, therapeutic coverage (of total population) and proportion of systematic non-adherence (SNA) for ivermectin mass drug administration (MDA) for the three intervention scenarios simulated for Togo\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cdiv align=\\\"\\\"\\u003e\\n \\u003ctable border=\\\"1\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" width=\\\"623\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 150px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eScenario\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd rowspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 102px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eVC efficacy\\u003c/strong\\u003e\\u003csup\\u003ea\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"3\\\" valign=\\\"top\\\" style=\\\"width: 300px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eIvermectin MDA therapeutic coverage\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd rowspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 71px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eSNA\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 100px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e1991 \\u0026ndash; 1995\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 100px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e1996 \\u0026ndash; 2001\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 100px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e2002 \\u0026ndash; 2030\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 150px;\\\"\\u003e\\n \\u003cp\\u003eMinimal (upper uncertainty bound)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 102px;\\\"\\u003e\\n \\u003cp\\u003e60%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 100px;\\\"\\u003e\\n \\u003cp\\u003e50%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 100px;\\\"\\u003e\\n \\u003cp\\u003e65%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 100px;\\\"\\u003e\\n \\u003cp\\u003e65%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 71px;\\\"\\u003e\\n \\u003cp\\u003e5.0%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 150px;\\\"\\u003e\\n \\u003cp\\u003eReference (average)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 102px;\\\"\\u003e\\n \\u003cp\\u003e75%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 100px;\\\"\\u003e\\n \\u003cp\\u003e50%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 100px;\\\"\\u003e\\n \\u003cp\\u003e65%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 100px;\\\"\\u003e\\n \\u003cp\\u003e75%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 71px;\\\"\\u003e\\n \\u003cp\\u003e2.5%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 150px;\\\"\\u003e\\n \\u003cp\\u003eEnhanced (lower uncertainty bound)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 102px;\\\"\\u003e\\n \\u003cp\\u003e90%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 100px;\\\"\\u003e\\n \\u003cp\\u003e65%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 100px;\\\"\\u003e\\n \\u003cp\\u003e75%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 100px;\\\"\\u003e\\n \\u003cp\\u003e80%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 71px;\\\"\\u003e\\n \\u003cp\\u003e1.0%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003c/table\\u003e\\n\\u003c/div\\u003e\\n\\u003cp\\u003e\\u003csup\\u003ea\\u003c/sup\\u003eFor Savanes, 100% VC efficacy simulations were also run for the three scenarios [32]. See Supplementary Material 1, Text S4 for further details, and Supplementary Material 2 for reported coverage of total population.\\u003c/p\\u003e\\n\\u003cp\\u003eA total of 100 model repeats were run for each of the three intervention scenarios, four endemicity levels, five regions and SIZ status. The mean of the 100 runs yielded mean microfilarial prevalence dynamics over time. Prevalence trends were visualized using the \\u0026ldquo;minimal\\u0026rdquo; and \\u0026ldquo;enhanced\\u0026rdquo; scenarios as the upper and lower uncertainty bounds, with \\u0026ldquo;reference\\u0026rdquo; scenario representing the average. Simulated trends are presented alongside survey prevalence estimates with 95%CIs per region and SIZ status to illustrate infection trends and compare model outputs with observations. The proportion of the population examined for \\u003cem\\u003eO.\\u0026nbsp;volvulus\\u003c/em\\u003e skin microfilariae decreased from \\u0026gt;80% at the beginning of the OCP to \\u0026lt;70% between 2006 and 2015 (Text S5, Figure S7). Table S6 lists the villages with recorded BMP. Infection trends of villages lacking BMP were visually compared to model outputs for all endemicity settings and intervention scenarios to infer their most likely initial endemicity level (Text S7).\\u003c/p\\u003e\\n\\u003ch2\\u003eElimination probabilities\\u003c/h2\\u003e\\n\\u003cp\\u003eFor simulation of EOT probabilities, MDA frequencies from 2018 (annual or biannual, depending on prefecture) were used. The probability of reaching EOT for each scenario, region and SIZ status was calculated as the percentage of 100 model runs yielding zero microfilarial prevalence 50 years after stopping MDA in 2024, 2027 or 2030 [40]. For Maritime, where MDA ended in some prefectures in 2014 and in all by 2020, simulations ceasing MDA in 2014 or 2020 were performed (Tables 1, S2). Five EOT probability categories were defined: \\u0026lt;5%, 6-19%, 20-59%, 60-89% and \\u0026ge;90%. Villages with projected EOT probabilities \\u0026lt;90% if MDA stops in 2027 were listed (Supplementary Material 2, Text S8). Prefecture-wide likelihoods of reaching EOT were calculated (Text S9).\\u0026nbsp;\\u003c/p\\u003e\"},{\"header\":\"RESULTS\",\"content\":\"\\u003ch2\\u003ePrevalence trends by region\\u003c/h2\\u003e\\n\\u003cp\\u003eFigures 2-6 present modelling results for the 140 OCP villages with recorded BMP estimates. Supplementary Material 1, Figures S8-S14 present results for villages without BMP estimates.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eSavanes\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eVillages with BMP estimates in Savanes prefectures were hypo- to mesoendemic in SIZ and meso- to hyperendemic in non-SIZ areas (Figure 2). Prevalence decline was primarily driven by VC with enhanced (90%) or 100% efficacy (Figures 2A-2E), eventually leading to \\u0026ge;90% EOT probability following initiation of MDA in hypo- to mesoendemic areas (Supplementary Material 2, Table S7). Some SIZ villages lacking recorded BMP (Oti River Basin) had high prevalence, following hyper- to holoendemic simulation trends (Figure S8).\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eKara\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eVillages in Kara (all prefectures in SIZ) with recorded BMP estimates encompassed all endemicity levels (Figure 3). The intervention scenarios best capturing infection trends were: minimal for hypoendemicity (Figure 3A), reference for mesoendemicity (Figure 3B), and minimal (M\\u0026ocirc; River Basin), reference (Kara River Basin) or enhanced (Kara River Basin) for hyperendemicity (Figure 3C). Holoendemic villages aligned with the enhanced (K\\u0026eacute;ran River Basin) intervention scenario (Figure 4D), with the model capturing the observed prevalence rebound after VC cessation. Two-fifths (30/74) of villages without BMP estimates followed hyper- to holoendemicity trends (Figure S10).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCentrale\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eVillages with recorded BMP in Centrale were hyperendemic in SIZ and ranged from hypo- to hyperendemic in non-SIZ areas. The SIZ hyperendemic villages (M\\u0026ocirc; River Basin) aligned closely with the reference intervention scenario (Figure 4A). Model projections for non-SIZ hypo- and mesoendemic villages (Figures 4B-4C) suggested a similar impact across intervention scenarios, likely because VC and MDA started roughly at the same time, reducing variability. Non-SIZ hyperendemic villages (Mono River Basin) followed the enhanced intervention scenario (Figure 4D). Villages without recorded BMP ranged from hypo- to holoendemic (Figures S11-S12). Nearly all SIZ villages (13/14) lacking BMP followed hyper- to holoendemic trends (M\\u0026ocirc; River Basin) (Figure S11).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003ePlateaux\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eVillages in Plateux (all non-SIZ) with recorded BMP were evenly distributed among hypo-, meso- and hyperendemicity (Figure 5). Model outputs were similar for hypo- and mesoendemicity, as in Centrale (Figures 5A-5D). Prevalence trends in hyperendemic villages were mostly captured by the enhanced intervention scenario, with some following the minimal and reference scenarios (Figures 5E-5F, Mono River Basin). Several villages without BMP estimates followed hyperendemic trends (Figure S13). Prefectures continued with annual MDA or switched to biannual MDA in 2014 (Table S2).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eMaritime\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eVillages in Maritime with recorded BMP were predominantly hypoendemic, and their modelled prevalence trends followed the reference and enhanced intervention scenarios (Figure 6A). The hyperendemic village depicted in Figure 6B was consistent with the enhanced scenario. Villages without BMP estimates generally exhibited low endemicity, except in Yoto and possibly Av\\u0026eacute; prefectures, where some trends suggested hyperendemicity following the enhanced intervention scenario (Figure S14).\\u003c/p\\u003e\\n\\u003ch2\\u003eElimination probabilities\\u003c/h2\\u003e\\n\\u003cp\\u003eSupplementary Material 2, Tables S7-S12 present EOT probabilities per region, baseline endemicity, SIZ status and intervention scenario. In Savanes, all SIZ hypo- to (100% VC efficacy) hyperendemic villages and nearly all (86%) non-SIZ villages are projected to have reached \\u0026ge;90% EOT probability by 2024. However, in the northwestern part of Savanes non-SIZ, surveys conducted in early to mid-1970s (not in the OCP database), indicated baseline hyperendemicity (Figure S1). As non-SIZ areas of Savanes did not receive biannual MDA and VC ceased in 1993 (Table 1), the projected EOT probabilities are \\u0026lt;5%. SIZ villages without BMP estimates following hyperendemic trends are projected to have \\u0026lt;90% probability of reaching EOT by 2024. Extending biannual MDA to 2027 or 2030 in putative hyperendemic villages does not improve their EOT probabilities, remaining at \\u0026lt;5%, 20-59%, and 60-89%, under minimal, reference, and enhanced interventions, respectively (Table S7).\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eIn Kara and Centrale, most hypo- and mesoendemic villages (regardless of SIZ status and intervention scenario) are projected to have reached \\u0026ge;90% EOT probability by 2024. Some non-SIZ mesoendemic villages of Centrale following the minimal scenario and annual MDA would only reach 60-89% EOT probability, even with MDA extended to 2030. Hyperendemic villages following the enhanced scenario are projected to have reached \\u0026ge;90% EOT probability by 2024. By contrast, those following the minimal or reference scenarios would have 5-19% or 60-89% EOT probability by 2024, respectively. If treatment continues until 2030, the former\\u0026rsquo;s EOT probability would increase to 20-59%. As in Savanes, holoendemic villages have \\u0026lt;5% EOT probability (Tables S8-S9).\\u003c/p\\u003e\\n\\u003cp\\u003eIn Plateaux, owing to its lower BMP compared to Kara and Centrale, VC started later and not all prefectures adopted biannual MDA. Hypoendemic villages (irrespective of treatment frequency) and mesoendemic villages following reference and enhanced scenarios with annual or biannual MDA, are projected to have reached \\u0026ge;90% EOT probability by 2024. The same applies to mesoendemic villages following the minimal scenario under biannual MDA. Mesoendemic villages following the minimal scenario and hyperendemic villages following the enhanced scenario under annual MDA, would have had 60-89% EOT probability by 2024. Hyperendemic villages following minimal and reference scenarios under annual MDA would only reach \\u0026lt;5% EOT probability by 2024 or 2030. Those following minimal and reference scenarios under biannual MDA would have reached, respectively, \\u0026lt;5% and 5-19% EOT by 2024, with the latter increasing to 20-59% if biannual MDA were extended until 2030. By contrast, hyperendemic villages following the enhanced scenario and already under biannual MDA could reach \\u0026ge;90% EOT if biannual treatment continues until 2030 (Table S10).\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eIn Maritime, only annual MDA had been implemented by 2018. Being the least endemic region, all hypoendemic villages, and those mesoendemic villages following the reference and enhanced scenarios, are projected to have reached \\u0026ge;90% EOT probability regardless of whether treatment ceased in 2014 or 2020. However, in one confirmed (with) and several putative (without BMP) hyperendemic villages, the EOT probability is 20-59% in 2020. Extending treatment in such villages to 2024 or 2030 would increase it to 60-89% (Tables S11-S12).\\u003c/p\\u003e\\n\\u003cp\\u003eSupplementary Material 2, Tables S13-S24 list villages by region, SIZ status, and river basin for which EPIONCHO-IBM projects EOT probabilities \\u0026lt;90% if MDA stops in 2027. Tables S25-S29 present the rationale and calculations of prefecture-wide likelihoods (joint probabilities) of achieving EOT. Figure 7 illustrates the (categorical) likelihood of reaching EOT if ivermectin MDA stops in 2027.\\u003c/p\\u003e\"},{\"header\":\"DISCUSSION\",\"content\":\"\\u003cp\\u003eModelling analyses of detailed spatiotemporal \\u003cem\\u003eO. volvulus\\u003c/em\\u003e prevalence data from the OCP and other sources (Text S2) provided a unique opportunity to quantify the combined impact of VC and ivermectin MDA in a former OCP country. The epidemiology of onchocerciasis in Togo has changed profoundly over nearly 50 years of intervention, with some prefectures on the verge of reaching EOT (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e7\\u003c/span\\u003e) and others projected not to reach EOT with current strategies. Our results illustrate the power of mathematical modelling in evaluating past, current and future epidemiology of onchocerciasis, to assist programmes in decision-making and resource allocation to maximise their chances of reaching the 2030 elimination goals.\\u003c/p\\u003e \\u003cp\\u003eWe identified regional epidemiological patterns, long-term prevalence declines, and subsequent increases in some cases. In Savanes non-SIZ, (hypo- to hyperendemic) villages with 90\\u0026ndash;100% VC efficacy had reached a very low microfilarial prevalence by the time MDA started (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e and S8). This contrasts with other regions where VC was likely less impactful, underscoring the need for combining VC and MDA. After VC cessation, hypo- to mesoendemic villages performed well under MDA. Annual MDA sustained previous gains in hyperendemic villages, but only biannual MDA led to further prevalence declines (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e\\u0026ndash;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e, S10-S12). Holoendemic villages experienced prevalence increases after VC cessation, in both data and model outputs, even with biannual MDA (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e, S9-S10).\\u003c/p\\u003e \\u003cp\\u003eAccording to EPIONCHO-IBM, achieving\\u0026thinsp;\\u0026ge;\\u0026thinsp;90% EOT probability by 2024 in hypo- and mesoendemic areas nationwide seems feasible, and stop-MDA surveys could start if not already underway. Conversely, modelled prevalence in areas with hyper- and holoendemic villages, such as the Oti River Basin (Savanes), and the K\\u0026eacute;ran and M\\u0026ocirc; River Basins (Kara and Centrale), show a stable pseudo-equilibrium since 2007 (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eA-\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eB, \\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eC-\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eD, \\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eA), and are unlikely to achieve EOT under the current (biannual) MDA strategy, even if continued until 2030 (Tables S7-S9). Infection prevalence of 0.1-1.0% in blackflies was found for these river basins (2015), and of 0.5\\u0026ndash;0.8% in M\\u0026ocirc; (2018\\u0026ndash;2019), indicating active transmission [\\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e41\\u003c/span\\u003e]. In non-SIZ (northwestern) Savanes, where VC started and ended early [\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e], surveyed villages (with or without BMP estimates) are scarce in our database (Figure S4). However, based on surveys indicating hyperendemicity in the 1970s (Figure \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003e), EOT likelihood in Tandjouar\\u0026eacute; and T\\u0026ocirc;ne prefectures is \\u0026lt;\\u0026thinsp;90% (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e7\\u003c/span\\u003e). Stop-MDA surveys in 2022 indicated some villages of potential concern in these prefectures [\\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eWhilst most of Maritime would likely have reached\\u0026thinsp;\\u0026ge;\\u0026thinsp;90% EOT probability by 2020, some villages without BMP estimates, mostly in Yoto Prefecture, followed hyperendemic trends with moderate (60\\u0026ndash;89%) EOT probability. Active transmission was confirmed in Yoto during the 2020\\u0026ndash;2023 stop-MDA survey, prompting focal biannual MDA [\\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003e \\u003cb\\u003eLimitations.\\u003c/b\\u003e Although baseline ABRs were reduced during VC by its assumed efficacy, they were modelled as bouncing back one year after VC cessation [\\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e]. Deforestation, particularly in western Plateaux and southern Centrale [\\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e43\\u003c/span\\u003e], may have led to secular changes in vector density [\\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e44\\u003c/span\\u003e] not considered in the model. However, in the M\\u0026ocirc; River Basin, 2015\\u0026ndash;2019 ABRs were 12,000\\u0026ndash;16,000 bites/person/year [\\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e41\\u003c/span\\u003e]. Although we modelled information from 400 villages, there may be many others, certainly those with \\u0026gt;\\u0026thinsp;2,000 people, for which we have no epidemiological data as they were only incorporated into the NOCP in 2018 [\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e]. Because we may not have fully captured within-region heterogeneity, our prefecture-wide EOT likelihood must be interpreted with caution. Also, EPIONCHO-IBM models closed populations, not accounting for movement of people and/or flies between villages or cross-border migration that could jeopardise EOT by re-introduction of infection from less-well controlled areas [\\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e].\\u003c/p\\u003e\"},{\"header\":\"CONCLUSION\",\"content\":\"\\u003cp\\u003eTogo has made considerable progress towards onchocerciasis EOT owing to VC and ivermectin MDA, switching to biannual frequency where necessary. However, areas with confirmed or putative high baseline endemicity pose challenges to achieving nation-wide EOT. EPIONCHO-IBM has proven its usefulness in interpreting epidemiological data, and supports decisions regarding stop-MDA surveys (e.g., in hypo- to mesoendemic areas with \\u0026ge;15 years of high-coverage MDA and/or biannual treatment). In hyper- and holendemic areas with low EOT probabilities (e.g., in Kara and Centrale), the model suggests that ATS [21] should be considered. In particular, biannual moxidectin MDA supplemented, if feasible, by \\u0026ldquo;slash-and-clear\\u0026rdquo; VC would be beneficial [22,40]. EPIONCHO-IBM could be used in other former OCP countries to inform policy decisions towards the 2030 elimination goals.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003ch2\\u003eCompeting interests.\\u003c/h2\\u003e\\n\\u003cp\\u003eAll authors declare no competing interests.\\u003c/p\\u003e\\n\\u003ch2\\u003eAdditional information\\u003c/h2\\u003e\\n\\u003cp\\u003eSupplementary information File 1 and File 2.\\u003c/p\\u003e\\n\\u003ch2\\u003eOpen Access.\\u003c/h2\\u003e\\n\\u003cp\\u003eFor the purpose of open access, the authors have applied a Creative Commons Attribution (CC BY) licence to any author-accepted manuscript version arising from this submission.\\u003c/p\\u003e\\n\\u003ch2\\u003eAuthor Contributions.\\u003c/h2\\u003e\\n\\u003cp\\u003eConceptualization: L.-J.A., M.-G.B. Data exploration: J.I.D H. Data Curation: J.-L.A. Formal analysis: L.-J.A. Investigation and methodology: L.-J.A., J.I.D.H., M.W., M.-G.B. Software: J I.D.H. Resources: R.N.B., A.S., M.-G.B. Visualization: L.-J.A., M.W., M.-G.B. Supervision: M.W., M.-G.B. Funding acquisition: M.-G.B. Project administration: R.N.B., M.-G.B. Writing \\u0026ndash; original draft: L.-J.A., M.-G.B. Writing \\u0026ndash; review and editing: L.-J.A., R.N.B., A.S., M.-D.M., K.P., I.G.T., S.A., M.D., P.G., J.I.D.H., M.W., M.-G.B.\\u003c/p\\u003e\\n\\u003ch2\\u003eAcknowledgements.\\u003c/h2\\u003e\\n\\u003cp\\u003eL.-J.A. was funded by La Caixa Foundation (grant B005782). M. W. and M.-G. B. acknowledge funding by the Bill \\u0026amp; Melinda Gates Foundation through the NTD Modelling Consortium (grants OPP1184344 and INV-030046). M.-G.B. acknowledges funding from the MRC Centre for Global Infectious Disease Analysis (grant MR/X020258/1), funded by the UK Medical Research Council (MRC). This UK-funded award is carried out in the frame of the Global Health EDCTP3 Joint Undertaking. We would like to thank the people of Togo who, over many years, participated in the surveys analysed in this paper. Special thanks go to Dr Paul Cantey for his introduction to the Togo team, and to Prof. Robert Colebunders for his support. Dr Natalie Vinkeles Melchers provided useful advice on the assumptions used for the control interventions implemented in Togo that informed Table\\u0026nbsp;1. We also acknowledge Dr Philip Milton for his guidance during the early stages of the work, and Mr Aditya Ramani for calculating the range of annual biting rates for the holoendemic settings presented in Supplementary Material 1. This paper is dedicated to the memory of Prof. Yao Kassankogno whose contribution to data availability was invaluable. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The corresponding authors had final responsibility for the decision to submit for publication.\\u003c/p\\u003e\\n\\u003ch2\\u003eData availability.\\u003c/h2\\u003e\\n\\u003cp\\u003eThe database containing the epidemiological data has been made publicly available by Vinkeles Melchers et al. [\\u003cspan class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e]. All information used for the analyses is contained in this database [\\u003cspan class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e], and the figures, tables, and Supplementary Material files of this paper.\\u003c/p\\u003e\\n\\u003ch2\\u003eCode accessibility\\u0026nbsp;\\u003c/h2\\u003e\\n\\u003cp\\u003eThe EPIONCHO-IBM model code is available at: \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://github.com/mrc-ide/EPIONCHO.IBM\\u003c/span\\u003e\\u003c/span\\u003e.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eSchmidt CA, Cromwell EA, Hill E, et al. The prevalence of onchocerciasis in Africa and Yemen, 2000-2018: a geospatial analysis. BMC Med \\u003cstrong\\u003e2022; \\u003c/strong\\u003e20:293.\\u003c/li\\u003e\\n\\u003cli\\u003eGBD 2021 Diseases and Injuries Collaborators. 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Summary of presentations and discussions of GONE webinar: Togo on its path towards the elimination of onchocerciasis (11 June 2024), \\u003cstrong\\u003e2024\\u003c/strong\\u003e. Available at: https://cdn.who.int/media/docs/default-source/ntds/onchocerciasis/global-onchocerciasis-network-for-elimination-(gone)/webinar-reports/gone-webinar-report-togo-jun-2024-eng-fr.pdf?sfvrsn=5e782f71_3\\u0026amp;download=true. Accessed 21 March 2025.\\u003c/li\\u003e\\n\\u003cli\\u003eGlobal Forest Watch. Location of tree cover loss in Togo. Available at: https://www.globalforestwatch.org/dashboards/country/TGO/?category=forest-change\\u0026amp;map=eyJjYW5Cb3VuZCI6dHJ1ZX0%3D. Accessed 21 March, 2025.\\u003c/li\\u003e\\n\\u003cli\\u003eWilson MD, Cheke RA, Flasse SP, et al. Deforestation and the spatio-temporal distribution of savannah and forest members of the \\u003cem\\u003eSimulium damnosum\\u003c/em\\u003e complex in southern Ghana and south-western Togo. Trans R Soc Trop Med Hyg \\u003cstrong\\u003e2002; \\u003c/strong\\u003e96:632\\u0026ndash;39. \\u003c/li\\u003e\\n\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":true,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":true,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"nature-portfolio\",\"isNatureJournal\":true,\"hasQc\":false,\"allowDirectSubmit\":false,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"\",\"title\":\"Nature Portfolio\",\"twitterHandle\":\"\",\"acdcEnabled\":false,\"dfaEnabled\":false,\"editorialSystem\":\"ejp\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":false},\"keywords\":\"onchocerciasis, vector control, ivermectin, elimination, modelling, Togo\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-6284820/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-6284820/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003eThe Onchocerciasis Control Programme in West Africa implemented vector control (VC) and ivermectin mass drug administration (MDA) to eliminate blindness. In Special Intervention Zones (SIZ), efforts were intensified. Togo aims to eliminate onchocerciasis transmission (EOT) by 2030. The stochastic EPIONCHO-IBM transmission model was used to project \\u003cem\\u003eOnchocerca volvulus\\u003c/em\\u003e microfilarial prevalence trends in Togo\\u0026rsquo;s five regions according to SIZ status, treatment coverage (65%-80% of total population) and VC efficacy (60%-100%). Model outputs were compared with microfilarial prevalence surveys (1970\\u0026ndash;2017, 400 villages) following four endemicity (baseline microfilarial prevalence) levels: hypoendemic (30%), mesoendemic (50%), hyperendemic (70%), and holoendemic (90%). EOT probabilities were calculated for 2024, 2027 and 2030. VC plus MDA substantially reduced prevalence. In holoendemic areas, this decline was not sustained after VC cessation despite biannual MDA. Baseline hypo- and mesoendemic areas can proceed with stop-MDA surveys (already underway). Highly endemic river basins would benefit from alternative treatment strategies (ATS). EPIONCHO-IBM captured Togo\\u0026rsquo;s onchocerciasis trends throughout five decades of intervention. While most areas of the country may no longer require MDA, some are unlikely to reach EOT with current intervention strategies, indicating the need for ATS. Our modelling approach could be used in other endemic countries to inform policy decisions towards the 2030 elimination goals.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e\",\"manuscriptTitle\":\"Reaching Elimination of Onchocerciasis Transmission with Long-term Vector Control and Ivermectin Treatment in West Africa: The Example of Togo\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-04-07 04:39:33\",\"doi\":\"10.21203/rs.3.rs-6284820/v1\",\"editorialEvents\":[],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"nature-communications\",\"isNatureJournal\":true,\"hasQc\":false,\"allowDirectSubmit\":false,\"externalIdentity\":\"NCOMMS\",\"sideBox\":\"Learn more about [Nature Communications](http://www.nature.com/ncomms/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://mts-ncomms.nature.com/\",\"title\":\"Nature Communications\",\"twitterHandle\":\"\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"ejp\",\"reportingPortfolio\":\"Nature Communications\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":false}}],\"origin\":\"\",\"ownerIdentity\":\"99fbcb1b-0e6e-423a-93d0-b8778eb11469\",\"owner\":[],\"postedDate\":\"April 7th, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"published-in-journal\",\"subjectAreas\":[{\"id\":46707506,\"name\":\"Health sciences/Diseases/Infectious diseases/Parasitic infection\"},{\"id\":46707507,\"name\":\"Biological sciences/Computational biology and bioinformatics/Computational models\"}],\"tags\":[],\"updatedAt\":\"2026-01-22T08:06:33+00:00\",\"versionOfRecord\":{\"articleIdentity\":\"rs-6284820\",\"link\":\"https://doi.org/10.1038/s41467-025-67451-8\",\"journal\":{\"identity\":\"nature-communications\",\"isVorOnly\":false,\"title\":\"Nature Communications\"},\"publishedOn\":\"2025-12-19 05:00:00\",\"publishedOnDateReadable\":\"December 19th, 2025\"},\"versionCreatedAt\":\"2025-04-07 04:39:33\",\"video\":\"\",\"vorDoi\":\"10.1038/s41467-025-67451-8\",\"vorDoiUrl\":\"https://doi.org/10.1038/s41467-025-67451-8\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-6284820\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-6284820\",\"identity\":\"rs-6284820\",\"version\":[\"v1\"]},\"buildId\":\"XKTyCvWXoU3ODBz1xrDgd\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}