Data-driven analyses of behavioral strategies to eliminate cysticercosis in sub-Saharan Africa.

BACKGROUND: The multi-host taeniosis/cysticercosis disease system is associated with significant neurological morbidity, as well as economic burden, globally. We investigated whether lower cost behavioral interventions are sufficient for local elimination of human cysticercosis in Boulkiemdé, Sanguié, and Nayala provinces of Burkina Faso. METHODOLOGY/PRINCIPAL
FINDINGS: Province-specific data on human behaviors (i.e., latrine use and pork consumption) and serological prevalence of human and pig disease were used to inform a deterministic, compartmental model of the taeniosis/cysticercosis disease system. Parameters estimated via Bayesian melding provided posterior distributions for comparing transmission rates associated with human ingestion of Taenia solium cysticerci due to undercooking and human exposure to T. solium eggs in the environment. Reductions in transmission via these pathways were modeled to determine required effectiveness of a market-focused cooking behavior intervention and a community-led sanitation and hygiene program, independently and in combination, for eliminating human cysticercosis as a public health problem (<1 case per 1000 population). Transmission of cysticerci due to consumption of undercooked pork was found to vary significantly across transmission settings. In Sanguié, the rate of transmission due to undercooking was 6% higher than that in Boulkiemdé (95% CI: 1.03, 1.09; p-value < 0.001) and 35% lower than that in Nayala (95% CI: 0.64, 0.66; p-value < 0.001). We found that 67% and 62% reductions in undercooking of pork consumed in markets were associated with elimination of cysticercosis in Nayala and Sanguié, respectively. Elimination of active cysticercosis in Boulkiemdé required a 73% reduction. Less aggressive reductions of 25% to 30% in human exposure to Taenia solium eggs through sanitation and hygiene programs were associated with elimination in the provinces.
CONCLUSIONS/SIGNIFICANCE: Despite heterogeneity in effectiveness due to local transmission dynamics and behaviors, education on the importance of proper cooking, in combination with community-led sanitation and hygiene efforts, has implications for reducing morbidity due to cysticercosis and neurocysticercosis.

Introduction

Recognized by the World Health Organization as a neglected tropical disease, human cysticercosis has substantial health and economic consequences in populations dependent on subsistence farming for food and income [1]. Human cysticercosis is a condition that results as cysticerci, or larvae of the parasite Taenia solium (T. solium), develop in the body’s tissues after people ingest T. solium eggs, and thus act as accidental intermediate hosts [2]. The usual life cycle of the parasite however involves pigs as intermediate hosts, and humans as final hosts. Pigs can develop cysticercosis upon ingestion of T. solium eggs, facilitated by free-roaming pig production practices and poor sanitation. Consumption of undercooked pork dishes prepared from infected pigs, in turn leads to T. solium taeniosis in humans, i.e. infection with the adult form of the tapeworm. Tapeworm carriers excrete parasite eggs when gravid proglottids are passed with the stool. Exposure to T. solium eggs, either in the environment, or through direct contact with taeniosis-infected individuals or self-infection, facilitated by open defecation, poor access to sanitation and hygiene, can lead to human cysticercosis. There is a general lack of data on taeniosis/cysticercosis generated from large epidemiological studies [3], although human cysticercosis has been reported in 22 countries across Africa and is considered endemic in most countries of Latin America and Southeast Asia [3,4]. In the high burden setting of Burkina Faso, the prevalence of active cysticercosis in villagers in 3 provinces was estimated at up to 11.5% [5].

T. solium has been estimated to incur 2.78 million DALYS in 2010, ranking number 4 out of 33 foodborne diseases, and having the higher rate of DALYs per 100,000 population in sub-saharan Africa of all foodborne infections evaluated [6]. When larvae of T. solium lodge in the central nervous system, a condition called neurocysticercosis develops and may cause symptoms including epilepsy, hydrocephaly, and stroke; the condition can be fatal [7,8]. Upon detection through brain imaging, neurocysticercosis may be treated with antiparasitic drugs or with anti-inflammatory drugs combined with symptom-specific treatment depending on the viability, number, and location of the cysts [9,10].

Intervention approaches for interrupting the taeniosis/cysticercosis transmission cycle have ranged from porcine vaccination [11] to ultrasonography diagnostic measures for pigs to improved sanitation infrastructure [12]. Less resource-intensive approaches have considered proper cooking strategies to remove the threat of infectious cysts from pork meat due to the sensitivity of adult T. solium parasites to temperature [13,14]. However, the lack of field evidence on which large-scale strategies are most sustainable and cost-effective has thwarted elimination of the morbidity associated with neurocysticercosis and financial losses associated with porcine cysticercosis [15].

Mathematical modeling has been increasingly used to inform intervention strategies against neglected tropical diseases in resource-constrained settings [16,17], although few models have been developed to simulate dynamic changes in the T. solium transmission cycle in response to human-, pig-, and/or environment-centered intervention programs [18]. Four methodologically unique transmission models [14,19-21] have been used to demonstrate the potential for attaining disease elimination across intervention scenarios. Three of these models [14,19,20] were implemented by incorporating epidemiological information from diverse settings or making hypothetical assumptions about generalized settings. Models informed by specific study settings could offer insight into context-sensitive intervention effectiveness.

We present a mathematical model of taeniosis/cysticercosis transmission to investigate the effect of a low-resource, human behavior-focused intervention, using field epidemiological data on disease prevalence and sanitation practices from three provinces of Burkina Faso. Specifically, we assess the impact of a cooking behavior intervention targeting market cookshop owners on reducing incidence of human cysticercosis. The cooking intervention was investigated alone and in combination with efforts to improve latrine use and basic hygiene. The model is the first to consider (1) the relative contributions to human cysticercosis of taeniosis carriers’ autoinfection versus environmentally mediated mechanisms and (2) heterogeneity in intervention impact due to behavior-epidemiologic differences across geographically proximal, yet socio-demographically varying endemic settings. Our findings identify critical drivers of transmission and progression of cysticercosis, while highlighting gaps in current knowledge.

Methods

Ethics statement

This study was approved by the University of Oklahoma Health Sciences Center Institutional Review Board (IRB/1419) and the Centre Muraz Ethical Review Board (14-0027-AFRICSANTE/DR). It was also approved for the statistical analyses of the data by the Université de Montréal (#CERSES-19-081-D). Written consent was obtained from all participants or pig owners from whom data was used for this model. Formal consent was obtained by parent or guardian for children aged 18 years old or less, but children aged 10 or more were asked for their assent.

A deterministic compartmental model was developed to represent the multi-host taeniosis and cysticercosis infection system (Fig 1 and S1 Equations). The model was informed by epidemiological data collected as part of cohort and prevalence case-control studies conducted in Burkina Faso [22-24]. The multi-host transmission model was implemented using Matlab version R2016a (9.0.0).

Fig 1

Compartmental model structure for multi-host taeniosis and cysticercosis disease system.

A proportion of people with cysticercosis (IH2) are assumed to be coinfected with taeniosis. Both autoinfection among those with taeniosis as well as consumption of infected pork by those with cysticercosis were recognized as mechanisms of coinfection.

Data

Description of the parent study

Data collected as part of a large cluster-randomized controlled trial aimed at estimating the effectiveness of an educational intervention to reduce human and porcine cysticercosis were used to parameterize the dynamic transmission model. Specifically, data on human antibodies to T. solium adult stages measured during an embedded prevalence case-control study conducted at baseline [22] and on the prevalence of active cysticercosis in humans measured during the 18-month pre-randomization follow-up visit [22,24] were used.

The parent study was conducted between February 2011 and December 2014 in three provinces of Burkina Faso: Nayala, Boulkiemdé, and Sanguié. The baseline and pre-randomization visits took place from February 2011 to January 2012 and from August 2012 to July 2013 (i.e. 18 months apart), respectively. The selection criteria and procedures for study villages, households, concessions (i.e. a gathering of households in a compound) and participants for the baseline visit have been described in detail elsewhere [5,24]. Briefly, two villages present on official maps, at least 5 km apart from other study villages and with at least 1000 inhabitants, were randomly selected from each pig-raising department in the three provinces. In each of the 60 villages, a census was conducted to determine the number of concessions where sows and piglets were raised, the number of concessions without pig raising, as well as the number of households per concession. Eighty concessions were sampled according to a stratified random sampling approach, with type of pig raised at the time of sampling as stratum (i.e., 10 concessions with sow raising, 30 concessions with piglet raising, 40 concessions with or without pig raising). In each selected concession, one household was randomly selected and one eligible individual (at least five years old, living in the village for at least one year, and not planning to move for the following three years) was randomly selected within each household and invited to participate in the study. In each village, sixty participants and all participants screening positive for epilepsy or severe chronic headaches at baseline were asked to provide a blood sample. During the pre-randomization follow-up, each participant was asked to provide a blood sample (60 per village) and to answer a socio-behavioral and screening questionnaire (20 additional subjects per village). In case the participant had moved away since the last visit, a person living in the same household was asked to participate in the study. At each visit, 40 pig owners (in the 40 randomly selected pig-raising concessions) were asked for their consent to take a blood sample on one of their pigs and were interviewed regarding their pig management methods.

Sources of data for different elements of the dynamic transmission model

Prevalence of active cysticercosis in humans

The pre-randomization visit data were used to estimate the prevalence of active cysticercosis in the area. Mass drug administration of albendazole and ivermectin as part of a national lymphatic filariasis elimination program had been gradually phased out starting in 2012 [25], and the last community-wide delivery of praziquantel for schistosomiasis control in the region occurred in 2010 (personal communication, health district data officers), while delivery to school-aged children every two years was ongoing in the region [24]. Our data showed an increase in the prevalence of active cysticercosis in the control group from baseline to the post-randomization visit [24], suggesting that the interruption of community-based delivery of MDA may have resulted in an increase in the prevalence of cysticercosis. Therefore, data from the pre-randomization visit, which were available for the 60 villages, were used as they may better reflect the endemic levels of cysticercosis in the population. We describe below the methods used to obtain the estimates needed to calibrate the model (Table 1).

Table 1

Data and terms informing the likelihood for the Bayesian melding model fitting, from pre-randomization visit, all groups.

Description	Equation using transmission model variables	Province-specific estimate	Sample size
Humans
Prevalence of active cysticercosis in humans	IH2/NH	B* = 6.7% (5.6–8.0);N* = 4.1% (2.7–5.9);S* = 3.4% (2.3–4.7)	B = 1555; N = 603; S = 844
Prevalence of current taeniosis in humans (adjusted for ME) a	[IH1+α×(IH2)]/NH	B = 3.5% (1.5–6.5);N = 2.6% (1.0–5.4);S = 2.3% (0.8–5.0)
Prevalence of active cysticercosis/current taeniosis coinfection in humans (adjusted for ME) a	[α×(IH2)]/NH	B = 2.4% (1.0–4.3);N = 1.4% (0.5–2.8);S = 1.2% (0.4–2.3)
Pigs
Prevalence of active cysticercosisb	IP/NP	B = 20.7% (4.2–47.8)N = 14.9% (1.0–40.5)S = 21.0% (4.3–48.8)	B = 857; N = 219; S = 643

*For B = Boulkiemdé; N = Nayala; S = Sanguié

a Estimates from Latent Class models, adjusting for misclassification error (ME)

b Uses calcified or degenerating cysts in specificity (Sp) estimation (considered as negative) and using priors from Chembensufo [26]

Sera from 3,075 eligible and consenting participants providing a blood sample at the pre-randomization visit were used. Blood samples were obtained from the antebrachium vein and cooled until further processing. Sera were collected within three days after blood collection and frozen and stored at −20°C until analysis. Serum samples were then tested for the presence of excretory–secretory circulating antigens of the metacestode of T. solium using the B158/B60 enzyme-linked immunosorbent assay (Ag-ELISA) [27]. This test has an estimated sensitivity of 90% (95% Bayesian credible interval [BCI]: 80; 99%) and a specificity of 98% (95% BCI: 97; 99%) for the detection of active human infection [28].

The prevalence of active cysticercosis was modeled as a binomial distribution with the number of individuals positive to the Ag-ELISA as the numerator and the total number of individuals tested in each province as the denominator.

Frequency of food and sanitation practices

Participants providing a blood sample also answered a questionnaire at the pre-randomization visit about sociodemographic factors and practices with regard to pork consumption, drinking water, sanitation, and self-reported tapeworm infection as well as knowledge of the life cycle of T. solium [22]. The distribution of sociodemographic factors and practices was similar between those who provided a blood sample and those who only answered the questionnaire. Therefore, data from the 3,002 participants who answered the questionnaire and provided a blood sample were used in the model.

Pig demographics

Rates of birth, natural death, and slaughter for pigs were derived from questionnaire data and personal communication with experts in swine medicine. From the questionnaire data, it was determined that approximately 40% of concessions had pigs and that 20% of pigs were sows kept for reproduction. This estimate is consistent with a Food and Agricultural Report about the status of the pig production sector in Burkina Faso published in 2012 [29]. Out of 100 living pigs present in a village at any point in time, 27 will die due to other causes before slaughter, at 0.26 years of age on average, and 73 will die upon being sent to abattoirs for slaughter, at 1.64 years of age on average ([29], personal communication, Sylvie D’Allaire). Pig birth rate was determined to account for seven piglets per farrowing and 1.05 litters per sow per year, based on questionnaire data and expert knowledge.

Prevalence of active cysticercosis in pigs

At the pre-randomization visit, serum samples were obtained from 1,719 pigs. Blood samples were obtained from the jugular vein and the sera were frozen and stored at -20°C until analysis with the Ag-ELISA described above. To estimate the prevalence of active cysticercosis in pigs, we had to take into account cross-reactions of T. hydatigena in the Ag-ELISA, due to its genus, not species-specific character [26]. We used data from a study where 452 pigs slaughtered in an abattoir located in Boulkiemdé province were inspected for the presence of T. hydatigena. This study found lesions of T. hydatigena in 8.8% of the inspected pigs [30]. This prevalence was similar to that found (10%) in a study conducted among 68 pigs of slaughtered age dissected as part of a study conducted in Zambia [31]. Therefore, we adjusted the Ag-ELISA results for the poor performance of the test in this setting using the sensitivity and specificity estimates found in the Zambian study. Using dissection as a gold standard, and considering the presence of only calcified cysts as negative for active cysticercosis, the Zambian study estimated a sensitivity of 91% (95%CI: 71% to 99%) and a specificity of 65.3% (95%CI: 48.5% to 77.3%) for the Ag-ELISA to detect active cysticercosis in pigs [31]. These values were used as priors in a Bayesian Latent Class model with one test and prevalence estimates adjusted for misclassification error were obtained using the method described in Joseph et al. 1995 [32]. The model was run in WinBugs 1.4.

Prevalence of taeniosis in humans

We used data from the baseline prevalence case-control study [21] to estimate the prevalence of taeniosis in humans. To this end, we used the proportions of participants seropositive to antibodies of taeniosis (i.e. exposed to taeniosis) among controls seropositive to active cysticercosis and those seronegative to active cysticercosis. This information was then used to estimate the proportion of the overall population currently with taeniosis alone or actively co-infected (i.e., both taeniosis and active cysticercosis). The sampling of participants included in the prevalence case-control study has been described in detail elsewhere [22,33]. Briefly, a questionnaire was administered to all participants to screen for epileptic seizures, epilepsy and worsening severe chronic headaches. Sera from participants screened positive who agreed to provide a blood sample and from the same number of control participants matched by age group, gender and village were analysed for the presence of taeniosis antibodies using the rES33 test [34]. This test using recombinant antigens for detecting taeniosis antibodies has a reported sensitivity of 94.5% and specificity of 96% [34]. Because we were interested in current infection with taeniosis, we used a prior sensitivity value of 98% (95%CI: 96% to 100%) and a prior specificity value of 93% (95%CI: 86% to 100%) (John Noh, personal communication).

Among the 269 control participants, 14 were found positive to the rES33 test. This information was combined with the sensitivity and specificity prior information to obtain an adjusted estimate of the proportion of participants with active taeniosis among those Ag-ELISA positive and Ag-ELISA negative using a Bayesian Latent Class method described in Joseph et al. 1995 [32]. The adjusted proportions of current taeniosis among Ag-ELISA positive and Ag-ELISA negative controls were combined with data from the pre-randomization visit to obtain the prevalence of participants with current taeniosis only and current taeniosis and active cysticercosis. The model was run in WinBugs 1.4.

Dynamic transmission model

Model structure

A deterministic, compartmental model for transmission in the multi-host, cysticercosis-taeniosis system was developed as a set of differential equations, with separate compartment structures for pigs and humans (Fig 1 and S1 Equations). The host systems were linked through environmentally mediated transmission of T. solium eggs, which was explicitly represented with a compartment designated for simulating the availability of viable eggs to susceptible humans and pigs. Model parameters are presented in Table 2.

Table 2

Parameter estimates for compartmental model of multihost cysticercosis-taeniosis system.

Parameter/ Quantity	Description	Raw Estimatea	Standardized monthly rate for parameter estimates	Detail, where applicable	Source(s)
bP	Birth rate for domestic pigs	1.47 per pig per year	0.123 per pig per month	7 pigs per year per farrowing x 1.05 farrowing per sow per year x 20/100 sows per total pig population*	[42–43]
ε	Slaughter rate for domestic pigs	0.45 per pig per year	0.038 per pig per month	See S1A Text and S1 Table for full explanation of derivation. 73% of pigs in the population will be slaughtered as follows: 60% are piglets with 10% sent to abattoir at age 1.5 years + 90% are piglets slaughtered at home at age 1 year + 40% are sows slaughtered at age 4 years	[26]
μP	Natural death rate for domestic pigs	1.02 per pig per year	0.085 per pig per month	Calibrated to achieve constant pig population
μM	Average time of meat at market before sale	2 days	0.067 month
bH	Birth rate for humans (Burkina Faso)	42.03/1,000 per year	0.004 per month		[44]
μH	Natural death of humans (Burkina Faso)	42.03/1,000 per year	0.004 per month	Set equal to the birth rate for closed model system	[44]
θ	Recovery after loss of cysticercosis infection	48/109 per year	0.037 per month		[31]
π	Development of mature tapeworm	1/2.5 per month	0.4 per month		[1]
τ	Proglottids shed into the environment	3 per day	90 per month		[2]
δ	Contribution of humans to environmental contamination	55,000 x 3 per day	4,950,000 per month	55,000 fertile eggs per proglottid x τ proglottids per day per shedding human	[36]
ω	Natural resolution of taeniasis	3/1000 per day	0.09 per month	τ proglottids/1000 proglottids per worm per day per person	[2,35]
ψ	Viability of eggs	0.75			[45–46]
α	Proportion of co-infected individuals (prevalence of co-infection / prevalence of active cysticercosis)	B: 35.8%N: 34.1%S: 35.3%		Derived from Table 1	[21]
σ1k	% of population USUALLY eating pork at a market in one’s own villageb,c	B: 8.1% (6.9–9.7)N: 2.7% (1.5–4.3)S: 6.1% (4.6–8.0)			[23]
σ2k	% of population USUALLY eating pork at another village’s marketb,c	B: 1.2% (0.8–1.9)N: 0.8% (0.3–1.9)S: 1.6% (0.8–2.7)			[23]
σ1h	% of population USUALLY eating pork at own homeb,c	B: 48.5% (45.9–51.0)N: 48.5% (44.4–52.6)S: 59.0% (55.5–62.3)			[23]
σ2h	% of population USUALLY eating pork at another home in the same villageb,c	B: 1.8% (1.2–2.6)N: 1.0% (0.4–2.2)S: 1.1% (0.5–2.0)			[23]
l	% reporting ALWAYS using a latrine to defecate during the past 18 monthsb	B: 10.3% (7.8–11.9)N: 9.7% (7.4–12.4)S: 8.0% (6.2–10.0)			[23]
ρ	Monthly rate of loss of viable eggs from environment			Fit
χP	Monthly rate of consumption of fecally contaminated soil by pigs			Fit as the product βEχP
χF	Monthly rate among humans of ingestion of food or water contaminated by eggs in the environment and contact with eggs directly on another human carrier (collectively, χF)			Fit as the ratio of χF/χP, assumed to be <1**
χA	Monthly rate of cysticercosis infections among individuals with taeniosis due to autoinfection			Calibrated as the ratio of χA/χP, assumed to be <χF/χP
βE	Probability of transmission upon consumption of environmental contamination (i.e., infected fecal matter)			Fit as the product βEχP
βM	Probability of transmission of T. solium from pork meat to humans			Fit as the product βMck
ck	Proportion of pork that is undercooked and consumed in the market			Fit as the product βMck
γP	Force of infection for domestic pigs	Eq 1		Province-specific	Calculated
γM	Force of infection for humans consuming infected meat	Eq 2		Province-specific	Calculated
ηM	Rate of transmission due to undercooking of pork meat	Eq 3		Province-specific	Calculated
γF	Force of infection for humans consuming fecal contamination	Eq 4		Province-specific	Calculated
γA	Force of infection for humans consuming fecal contamination	Eq 5		Province-specific	Calculated

a All standardized to month-1 during model implementation.

b Province-specific practice parameters using questionnaire data from the 3,002 participants providing a blood sample at the pre-randomization visit.

c For pork consumption estimates, data presented as % (95% Confidence Interval). Only the point estimate was included in the model for each parameter.

* Additional detail, including dimensional analysis for bP, available in S1B Text.

** This assumption was based on the authors’ understanding of behavioral exposure to soil contaminated with T. solium eggs for pigs versus humans. Since pigs spend the majority of time roaming to find their own food (in the dry season) or tethered (in the short wet season) with regular exposure to sources of environmental contamination, these hots were expected to have higher contact with T. solium eggs than humans, whose environmental exposure would be, for example, from latrine use, shaking contaminated hands with an infected individual, or consumption of contaminated food—behaviors being intermittent throughout the day and at dosage levels less than walking or laying on contaminated soil.

Porcine hosts

Live pigs were represented in two states—susceptible (S) and infected (I)—and either died naturally at a rate μ or were slaughtered at a rate ε. Slaughtered pigs were uninfected (S) or infected (I) and transiently remained available as meat. The size of the live pig population was assumed to be constant, with the birth rate equal to the sum of the natural death rate and the slaughter rate. Derived from household-level survey data (See Data section in Methods), the initial conditions (Table 3) for the pig population were based on the mean number of pigs per household and the proportion of the human population reporting pig ownership.

Table 3

Province-specific initial conditions for population sizes.

Population	Province
	Boulkiemdé	Nayala	Sanguié
Human a	700,924	227,112	410,555
Pig b	280,370	90,845	164,222

a Source: OCHA Regional Office for West and Central Africa.

b Assuming that 40% of concessions have pigs.

Susceptible pigs become infected with cysticerci according to the force of infection (γ), which depends on the probability of transmission given ingestion of each T. solium egg (β) and the density-dependent rate of consumption of fecally contaminated soil (χ): where E represents the number of viable eggs shed by humans with taeniosis and available in the environment, as described in a later section. Susceptible and infected pigs were assumed to be slaughtered at equal rates and their meat was likewise assumed to be consumed at the same rate.

No compartment was included to capture the state of pre-patency. Data from pig cysticercosis in the study area suggest that infection occurs early in the life of a pig in this setting and is ongoing. Indeed, it was observed that the prevalence was above 40% and did not increase after the age of 3 months. Therefore, even though there is a pre-patent period, most pigs that will become infected will have active cysts by age 1, 1.5 or 4 years old when they are slaughtered and consumed by humans.

Human hosts

Initial human population conditions reflected available census data for the three provinces (Table 3). The human population was held constant, with equal birth and death rates, and was divided across compartments based on infection status for taeniosis (IH1) or cysticercosis (IH2). A proportion (α) of those with cysticercosis were assumed to be co-infected with taeniosis. Co-infection was not explicitly modeled as a separate compartment due to lack of data on temporality of first versus second infections (Fig 1).

Pork-eating individuals susceptible to both taeniosis and cysticercosis (S) ingest T. solium cysticerci according to the frequency-dependent rate: given the number of pigs with active cysticercosis slaughtered for meat (I), the total number of pigs slaughtered for meat (N) and η is an expression for the rate of transmission due to undercooking of pork meat. We define the expression as and where β represents the probability of transmission of T. solium from pork meat to humans, where σ and c are the proportion of the population eating pork and the proportion of pork that is undercooked, respectively, in the market (subscript k) and at home (subscript h). We assumed that pork consumed at home was always cooked at a temperature sufficient for killing the parasite. That is, we set c = 0. The assumption is consistent with information received at the study sites, as pork prepared at home is in the form of stews and boiled for long periods of time. Our data from interviews of mothers show that 98.5% of women preparing pork for the household boils the meat (3107/3156 mothers preparing pork). We further distinguished among the proportion of the population reporting most frequent pork consumption in markets in the same village (subscript 1k) versus another village (subscript 2k) and in their own homes (subscript 1h) versus another home (subscript 2h), with the former allowing for evaluation of village-level intervention that could be expected to only affect cooking behaviors within a village (described further in the section on ). Market-based pork meals in Burkina Faso include consumption of roasted meat (porc-au-four) or meat stews from street vendors and cookshops. Meat is often prepared in mud ovens for varying periods of time and at varying levels of heat.

Those individuals ingesting infected meat (E) will develop taeniosis and begin shedding T. solium eggs (I) at a rate of π which accounts for the period of parasite development. The rate of natural loss of infection will be dictated by the number of proglottids per worm and rate of shedding. Humans with taeniosis will naturally revert to being susceptible with a rate ω which corresponds to the days for all proglottids that an adult worm will produce in its lifetime to be shed.

Human may acquire cysticercosis via three routes (direct transmission through contact with taeniosis infected individuals, indirect transmission through the environment, and autoinfection), which differentially contribute to population-level prevalence. Infections through (1) direct contact with infected individuals (e.g., through contact with eggs on the hands of a taeniosis carrier) or (2) indirect contact through the environment (e.g. contaminated food or drinking water) have been attributed to a higher number of infections than those associated with (3) direct self-infection, or autoinfection, among individuals with taeniosis.[1] Autoinfection is considered both in terms of real auto-infection (through reverse peristaltic movements in the bowel) and the self-infection due to poor hygiene (so-called external auto-infection).

The transition from the compartment of individuals susceptible to both taeniosis and cysticercosis (S) to that with individuals with cysticercosis (I) is the result of environmentally mediated infections or direct contact with infected individuals. This density-dependent rate of cysticercosis transmission to entirely susceptible humans (S) depends on the probability of transmission given ingestion of each T. solium egg (β) and the combined rate among humans of ingestion of food or water contaminated by eggs in the environment and contact with eggs directly on another human carrier (collectively, χ) and was given by

Cysticercosis among individuals with taeniosis (I) is assumed to occur from autoinfection (at a rate χ), direct transmission, or an environmentally mediated route (collectively, χ) according to:

In addition, the pathway by which individuals with cysticercosis develop taeniosis was not modeled explicitly, although a small percentage of individuals were expected to experience co-infection through this route. The proportion (α) of those with cysticercosis who also had taeniosis therefore reflected both individuals who transitioned from I to I at a rate γ or who were already in I when exposed to contaminated pork meat. Both individuals with taeniosis only (I) and co-infected individuals contributed to the number of eggs shed into the environment as described in the next section.

Degeneration of all tissue cysts results in the movement of individuals to the susceptible compartment (S) at a rate θ, which we define as loss of infection.

Environmental compartment

The ET compartment represents the number of viable eggs by which humans and pigs can become infected and develop cysticercosis. Individuals with taeniosis only or co-infected with taeniosis and cysticercosis are expected to release δ eggs, which depends on the number of proglottids shed and eggs released. Each person with taeniosis typically harbors one adult worm composed of 1,000 proglottids on average [35]. Up to five proglottids are shed each day with 30,000–90,000 eggs released per proglottid [36-38]. Only a percentage of released eggs are viable (ψ) and accessible for infecting hosts (l). Accessibility is related to the proportion of the population not reporting use of latrine or other improved sanitation facility for defecation (Table 2).

The number of viable and available eggs in ET is therefore given by where ρ represents the monthly rate of decay of egg viability.

Intervention approaches

The effectiveness of behavioral change intervention strategies in reducing the prevalence of active cysticercosis among humans was considered. Specifically, the interruption of T. solium transmission through pork cooking strategies and the interruption of exposure to T. solium eggs, both through environmentally mediated mechanisms and auto-infection, were modeled independently and in concert to assess whether behavior change could eliminate active cysticercosis from the study population.

Cooking to an adequate temperature was assumed to reduce the proportion of pork that is undercooked (c) by a factor of E. The reduction was specifically applied to the proportion of pork consumed in the markets of the village of residence (σ1) to account for a village-level intervention that may not extend to outside villages. That is the rate of transmission due to undercooking of pork meat (), after accounting for the assumption c = 0, becomes β×c×[(1−E)×σ1+σ2].

Improvements in sanitation were assumed to be associated with behavioral changes in response to the education intervention used in the cluster randomized controlled trial of the parent study [23]. Improved sanitation was expected to reduce the rate of transmission associated with human exposure to T. solium eggs (β) by a factor of E. That is, the rate of transmission from eggs in the environment or through contact with someone with taeniosis to humans or to pigs becomes (1−E)×β with some hygiene or sanitation intervention.

For baseline (no intervention), the model was run to equilibrium using, as inputs, fixed parameters (Table 2) and acceptable posterior parameter sets identified during the fitting process and, as the output, the prevalence of active cysticercosis (per 1,000 population) at the equilibrium. For each intervention approach, the model was run to equilibrium with percent reductions in individual or multiple rates of transmission, according to our assumptions for how interventions would impact transmission, to represent the individual and combined intervention strategies, respectively, under consideration. The output of the intervention scenarios was likewise the prevalence of active human cysticercosis once the model reached equilibrium. In this way, we considered the long-term impact of routine and uniform implementation of interventions in endemic areas rather than the impact of pulse implementation or of time-dependent changes in implementation coverage.

For each intervention approach, the probability of reduction in prevalence to below a threshold of one case per 1,000 population was determined. In the absence of an elimination target from the World Health Organization, we defined this threshold for “elimination as a public health problem” [39]. The threshold was assessed using the average of the model output across the 1,000 sampled parameter combinations. Interventions were assumed to immediately and uniformly achieve a given reduction in transmission.

Model fitting algorithm

The model was parameterized using published epidemiological data and data from Burkina Faso (See Data section of Methods, Table 2). For each of the three provinces (j), four quantities for which limited prior data exist and which were expected to vary by setting were fitted using a three-term log likelihood equation: based on the prevalence (p) of disease states derived from the model, as designated in Table 1. The three disease states were active cysticercosis in humans, current taeniosis in humans, and active cysticercosis in pigs (Table 1). A beta-binomial distribution was assumed, accounting for the number of individuals in the sample from the field data for disease state j (n) and the number of individuals observed for the disease state j (x). The four quantities sampled included the parameter for the monthly rate of decay of egg viability in the environment (ρ), as well as three aggregate quantities: (1) the product of the probability of transmission of T. solium cysticerci from pork meat to humans and the rate of undercooking in markets (βc), (2) the product of the probability of transmission given ingestion of each T. solium egg and the rate of consumption of fecally contaminated soil by pigs (βχ), and (3) the ratio of the rate among humans of ingestion of food or water contaminated by eggs in the environment and contact with eggs directly on another human carrier versus the rate of pigs’ consumption of fecally contaminated soil (χ/χ). The use of aggregate quantities was due to the lack of prior information to appropriately constrain the values of individual parameters for model identifiability.

A Bayesian melding approach [40] was used to randomly sample a set of parameter estimates from independent prior distributions and evaluate the model output according to the likelihood equation (). Likelihoods were initially generated for 150,000 iterations of the model. The model was then implemented with 1,000 parameter sets, probabilistically sampled from the distribution of 150,000 according to the weight of their normalized negative log likelihood values. The melding approach was implemented separately for Boulkiemdé, Nayala, and Sanguié provinces. This procedure was repeated across a pre-defined set of parameter estimates for χ/χ: 0.0025, 0.005, 0.01, 0.025, 0.05, 0.10, 0.25, 0.5, and 0.75. For each province, χ/χ was tuned between the two parameter estimates providing the best fit for further improvement. The mean of the log likelihoods generated from the posterior parameter sets for each χ/χ value was sequentially compared with that for other t values to determine which provided the best fit to the data.

For all iterations of model implementation, the model was run for 10,000 timesteps (i.e., months) and the results were evaluated to assess whether endemic conditions had been reached. If the difference in prevalence of cysticercosis (IH2) in the human population at t = 10,000 and t = 9,990 was <0.000001, the model was assumed to have reached dynamic equilibrium. If the condition was not met, the model was run for an additional 10,000 timesteps and re-evaluated. The process was repeated iteratively for a maximum 50,000 timesteps, and all iterations converged to equilibrium within that period.

We defined the rate of taeniosis transmission to humans upon consumption of infected pork by Therefore, the ratio of η/η would represent the relative rate of transmission due to undercooking in Boulkiemdé as compared to that in Sanguié. The 95% Fiellers confidence interval [18] and a t-test for the ratio of means of two independent samples were calculated.

Results

Model fit and province-specific parameterization

On average, the model-predicted average prevalence of active human cysticercosis and current human taeniosis for all provinces and across parameter sets was reflective of the data, in terms of both point estimates and confidence intervals (Fig 2). Modeled estimates for cysticercosis in pigs generally included a wider range of values compared to those for human cysticercosis and taeniosis, although this observation was consistent with the 95% confidence intervals from the study data, which were also wider for the pig data than the human data (Table 1). Prior to intervention, the model-estimated average prevalence of human cysticercosis in Boulkiemdé, Nayala, and Sanguié was 6.7%, 4.5%, and 3.6%, respectively. Average prevalence of current human taeniosis in Boulkiemdé, Nayala, and Sanguié was estimated as 3.5%, 2.7%, and 2.3%. Estimates for average prevalence of active cysticercosis in pigs were 24.1%, 18.9%, and 23.7% in Boulkiemdé, Nayala, and Sanguié, respectively.

Fig 2

Model fit to data.

The white circles and grey error bars are the point estimates and 95% CIs from the data. The violin plots (with embedded boxplots) are the model results. The point estimates, which were used for the likelihood, are close to the medians and means of the model output. The distribution of model output for cysticercosis in pigs and taeniosis in humans generally falls within the data CIs for those variables. The model is producing a larger range of values for active human cysticercosis than is observed in the data.

Province-level variations in the results of the model fitting process reflect the role of context-specific behavior in multi-host taeniosis and cysticercosis transmission dynamics (Fig 3). On average, the aggregate parameter (βχ) was lowest in Boulkiemdé and comparable for Sanguié and Nayala (Distributions provided in Table 2). Given that β is a biological parameter that could be assumed to be uniform across provinces, differences across the observed distributions for βχ were interpreted as relative, province-specific differences in rates of consumption of fecally contaminated soil by pigs (χ). That is, pigs in Sanguié and Nayala were more often consuming T. solium eggs from the environment than were pigs in Boulkiemdé. Across all settings, the rate of human ingestion of food or water contaminated by eggs in the environment and contact with eggs directly on another human carrier was considerably lower than that of pig consumption of eggs in the environment—that is, χ/χ << 1. On average, the ratio χ/χ was estimated to be lower in Sanguié than Boulkiemdé and Nayala. Given the previously stated observations about βχ, human ingestion of food or water contaminated by eggs in the environment and contact with eggs directly on another human carrier was occurring at a relatively lower rate in Sanguié than in Nayala. Compared to both Boulkiemdé and Nayala, χ in Sanguié was relatively greater than χ Moreover, the aggregate parameter (βc) was found to be higher in Nayala than in Boulkiemdé and Sanguié. As β is a biological parameter, the observed variation is attributable to differences in the proportion of pork meals undercooked in markets (c), with the model suggesting that undercooking was more prevalent in Nayala than in the other provinces. The fitted parameter distributions for the rate of loss of viable eggs from the environment (ρ) were relatively consistent across provinces.

Fig 3

Results of Bayesian melding model fitting procedure for the three study provinces in Burkina Faso: Sanguié, Boulkiemdé and Nayala.

Four, province-specific quantities (i.e., monthly rate of decay of egg viability in the environment (ρ), the product of the probability of transmission of T. solium cysticerci from pork meat to humans and the rate of undercooking in markets (βc), the product of the probability of transmission given ingestion of each T. solium egg and the rate of consumption of fecally contaminated soil by pigs (βχ), and the ratio of the rate among humans of ingestion of food or water contaminated by eggs in the environment and contact with eggs directly on another human carrier versus the rate of pigs’ consumption of fecally contaminated soil (χ/χ)) were fit using data on three outcomes (i.e., active cysticercosis in humans, active cysticercosis in pigs, and current taeniosis in humans).

For Sanguié, the model best represented the data when the ratio of the rate of autoinfection to the rate of pigs’ consumption of eggs in the environment (χ/χ) was 0.065. In contrast, for Boulkiemdé and Nayala, the model best represented the data when the ratio χ/χ was 0.75 and 0.125, respectively. The calibrated values for χ/χ correlated with the prevalence of current taeniosis—highest in Boulkiemdé and lowest in Sanguié.

Transmission due to undercooking

The rate of taeniosis transmission to humans upon consumption of infected pork η accounted for where pork consumption occurred, with undercooked meat assumed to only be available in market cookshops (). Transmission due to undercooking in Nayala was estimated to be 1.63 times that in Boulkiemdé (95% CI: 1.59, 1.67; p-value < 0.001) and 1.54 times that in Sanguié (95% CI: 1.51, 1.57; p-value < 0.001). Transmission due to undercooking (i.e., taeniosis infection due to consumption of infected pork) in Sanguié was found, on average, to be 6% higher than that in Boulkiemdé (95% CI: 1.03, 1.09; p-value < 0.001).

Post-intervention model findings

In general, the prevalence of active cysticercosis in humans was more effectively reduced through interruption of exposure to T. solium eggs than through interruption of consumption of T. solium cysticercosis in undercooked pork meat for the same coverage levels (Fig 4).

Fig 4

Impact of behavioral change interventions on active cysticercosis infections.

(A) Changes in the prevalence of active cysticercosis due to reductions in consumption of Error bars represent one standard deviation above the mean. Horizontal, gray bars represent average, pre-intervention prevalence of active cysticercosis by province (See Table 1).

In Sanguié and Nayala, elimination (i.e., elimination as a public health problem) of active cysticercosis in humans was achieved, on average, upon a 62% and 67% reduction, respectively, in the rate of undercooking of pork meat. Elimination could be achieved with reduction of undercooking in Boulkiemdé by 73% (Fig 4A). More modest reductions of 25%, 26%, and 30% in human exposure to T. solium eggs, such as through community-led sanitation programs, were associated with cysticercosis elimination in Sanguié, Nayala, and Boulkiemdé, respectively (Fig 4B).

Intervention leading to at least 5% reduction in consumption of undercooked pork combined with less than 25% reduction in exposure to T. solium eggs in the environment was associated with elimination in Sanguié and Nayala (Fig 5A). Elimination in Boulkiemdé warranted at least 5% reduction in consumption of undercooked pork, combined with more than 25% but less than 50% reduction in environmental exposure to T. solium eggs. More aggressive campaigns against undercooking in markets, leading to 50% reductions in undercooking, led to elimination across all three provinces if combined with reductions of about 10% in environmental exposure to T. solium eggs. Boulkiemdé—where transmission due to undercooking was estimated as significantly lower than in Nayala and Sanguié—required more aggressive intervention to achieve elimination than the other provinces in all scenarios, while elimination was achieved in Sanguié with the least aggressive intervention.

Fig 5

Combined impact of pork cooking and latrine use interventions on active cysticercosis.

(A) 5% reduction in exposure to Bars represent the average prevalence across simulations with 1,000 parameter sets. Error bars represent one standard deviation above the mean.

Discussion

The multi-host taeniosis/cysticercosis disease system includes multiple routes of transmission that afford opportunities for interrupting exposure to the different infectious stages of the parasite. Explicitly modeling the different hosts and routes of transmission allows for assessing targeted interventions in terms of their potential impact in eliminating human morbidity associated with cysticercosis. We found that reductions in transmission associated with interventions focused on changing behaviors, rather than introducing pharmaceutical tools or infrastructural innovations, is enough to eliminate active cysticercosis across different transmission settings in Burkina Faso. Combined approaches targeting both sanitation practices and cooking behaviors and henceforth interrupting multiple transmission routes achieved elimination at lower effectiveness levels than would be required by the individual interventions. Specifically, reductions of around 25% in exposure to T. solium eggs for both human and pig hosts, in combination with a 5% reduction in undercooking of pork in markets, were associated with universal elimination.

Existing modeling work on the public health burden of T. solium infection has increasingly been applied to consider a range of intervention strategies [17]. However, the lack of large-scale field data has led to assumptions about the effectiveness of the intervention and the baseline behaviors that are being intervened upon. Thus, existing models remain largely focused on theoretical populations. A recent review of mathematical models for T. solium identified gaps in modeling approaches and advocated for expanded, field-driven force-of-infection, population-based modeling [17]. Our model, including parameters used to inform province-specific practices around pork consumption and latrine use, extends existing work in a more field-informed and data-driven way to investigate potentially more logistically and economically feasible intervention. Our results emphasize the importance of accounting for local practices in assessing the potential of any intervention.

Boulkiemdé had the highest prevalence of active cysticercosis in humans and of taeniosis. Despite it being the highest burden setting, our findings suggest that transmission due to consumption of undercooked pork in market cookshops was less in Boulkiemdé than the other study settings per our posterior distributions for the aggregate parameter for the product of the probability of transmission of T. solium cysticerci from pork meat to humans and the rate of undercooking in markets (βc); since Nayala had a lower baseline prevalence of active cysticercosis in pigs than in Boulkiemdé, a higher rate of undercooking did not necessarily translate into a higher prevalence of taenioisis or human cysticercosis in Nayala. Likewise, the proportion of the population reporting latrine use to defecate was highest in Boulkiemdé. Thus, the investigated, human-focused interventions had incrementally less impact on disease transmission in this province than in Sanguié and Nayala. Pig-focused interventions could have greater impact in Boulkiemdé.

The results from this model become very useful in elucidating the observed effectiveness of the educational intervention tested as part of the clustered randomized controlled trial conducted in these villages. The trial showed that the intervention was most effective in Sanguié and Nayala, but not in Boulkiemdé [23]. The model suggested that more intensive improvements in latrine use and pork cooking habits were needed in Boulkiemdé than in Nayala and Sanguié to eliminate the infection (Fig 4). Further investigation into the interplay between transmission dynamics and behavior across settings is warranted. The model has offered insights that can be incorporated into future field trials [41].

While we have aimed to establish a modeling framework that incorporates field data and expertise, it is recognized that the results presented here reflect simplifying assumptions that would benefit from additional epidemiological data, but also information on social aspects of the settings where the infection is present, in future iterations.

Model limitations

The results presented here reflect several simplifying assumptions. For instance, future iterations of the model may account for changes in the pig and human populations over time. Also, the model did not account for spatial heterogeneity in the distribution of T. solium eggs throughout the environment and thus the differential exposure of humans and pigs to infection. There are currently no tests available to detect eggs in the environment (i.e. soil, water, objects, etc.), although incorporating it will remain a future direction for the model framework. Likewise, the current model does not account for heterogeneity in the burden of porcine cysticercosis infection. Without data on porcine parasite load or exposure to T. solium eggs (i.e., rate of ingestion as the distribution of dosage across pig populations in each province), future work could introduce distributional assumptions, starting with consideration of an overdispersed distribution to reflect differential probability of exposure to high versus low dosages or differential burden of parasite load across the porcine population. Moreover, the force of infection in the pig population does not reflect age-specific contributions to transmission by infected pigs. Future iterations of the model, given available data, might be structured to capture age dynamics of transmission in pig hosts and not overestimate the contribution to transmission of slaughter-age pigs. While the added complexity may not be relevant in all cases, it could have implications for the evaluation of pig-targeted interventions. The sensitivity of the model results around human prevalence to distributional assumptions around differential burden or exposure among pigs, whether age-specific or population-level, could be explored.

The lack of data to inform individual parameters led to decisions around the structure and interpretation of our model. Specifically, the use of aggregate parameters was intended to maintain the model structure with all individual parameter components defined so that it can be used to answer more nuanced questions in the future, as additional data to inform components become available. However, by fitting aggregate quantities, interpretation of the parameter distributions—particularly the absolute values—is limited and it is difficult to pinpoint exact relationships across provinces for the individual component parameters.

Moreover, we modeled pulse intervention versus change in transmission through gradual interruption of exposure routes. The findings reflect expected reductions in prevalence of active cysticercosis when given percent reductions are attained. Our goal was to consider the potential utility of interrupting different transmission routes so that the feasibility and logistics of interventions with high potential for elimination of cysticercosis as a public health problem could be investigated by field experts to provide more information that could be fed into the model with future results iteratively reflecting logistical and epidemiological ground truths.

Conclusions

Mathematical modeling of transmission within the multihost, taeniosis/cysticercosis system offers the potential to investigate novel intervention strategies working towards elimination of highly morbid neurocysticercosis. Efforts to address cooking and sanitation behaviors in settings with high prevalence of infected pigs and open defecation could successfully eliminate the disease, as an alternative to treatment and vaccination approaches. Field data on the effectiveness of education campaigns in settings with prevalent cysticercosis would enhance future model findings to inform context-specific strategies.

Transmission Model Equations.

(DOCX)

Click here for additional data file.

A Description of Derivation of Slaughter Rate for Domestic Pigs (ε). B Dimensional Analysis for Birth Rate for Domestic Pigs (bP).

(DOCX)

Click here for additional data file.

Description of Derivation of Slaughter Rate for Domestic Pigs (ε).

(DOCX)

Click here for additional data file.

5 Sep 2020

Dear Dr. Carabin,

Thank you very much for submitting your manuscript "Data-driven analyses of behavioral strategies to eliminate cysticercosis in sub-Saharan Africa" for consideration at PLOS Neglected Tropical Diseases. As with all papers reviewed by the journal, your manuscript was reviewed by members of the editorial board and by several independent reviewers.

Our apologies for the time taken for our response, but the disruptions caused by the ongoing public health emergency r unanticipated delays in completion of the external reviews. In light of the reviews (below this email), we would like to invite the resubmission of a significantly-revised version that takes into account the reviewers' comments.

We would like to see the issues mentioned by all the reviewers to be addressed, including the concerns raised by reviewer 3 regarding the model equations and the discussion.

We cannot make any decision about publication until we have seen the revised manuscript and your response to the reviewers' comments. Your revised manuscript is also likely to be sent to reviewers for further evaluation.

When you are ready to resubmit, please upload the following:

[1] A letter containing a detailed list of your responses to the review comments and a description of the changes you have made in the manuscript. Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.

[2] Two versions of the revised manuscript: one with either highlights or tracked changes denoting where the text has been changed; the other a clean version (uploaded as the manuscript file).

Important additional instructions are given below your reviewer comments.

Please prepare and submit your revised manuscript within 60 days. If you anticipate any delay, please let us know the expected resubmission date by replying to this email. Please note that revised manuscripts received after the 60-day due date may require evaluation and peer review similar to newly submitted manuscripts.

Thank you again for your submission. We hope that our editorial process has been constructive so far, and we welcome your feedback at any time. Please don't hesitate to contact us if you have any questions or comments.

Sincerely,

Siddhartha Mahanty, M.B.B.S., M.P.H

Associate Editor

PLOS Neglected Tropical Diseases

Marco Coral-Almeida

Deputy Editor

PLOS Neglected Tropical Diseases

***********************

Reviewer's Responses to Questions

Key Review Criteria Required for Acceptance?

As you describe the new analyses required for acceptance, please consider the following:

Methods

-Are the objectives of the study clearly articulated with a clear testable hypothesis stated?

-Is the study design appropriate to address the stated objectives?

-Is the population clearly described and appropriate for the hypothesis being tested?

-Is the sample size sufficient to ensure adequate power to address the hypothesis being tested?

-Were correct statistical analysis used to support conclusions?

-Are there concerns about ethical or regulatory requirements being met?

Reviewer #1: The manuscript "Data-driven analyses of behavioral strategies to eliminate cysticercosis in sub-Saharan Africa" offers an interesting and innovative methodology to study disease dynamic interactions based on community data. The reported results offer sufficient evidence to implement feasible strategies at a taeniasis/cysticercosis control program for researchers and decision-makers. However, I found that a small set of model parameters probably need to be corrected and probably redefined. Specifically in pig demography. Birth rate according to the data each sow gives birth 7 piglets per year, which means that for two years a sow will have 14 piglets and she will be 3 years old (so a probable rate 14/3 almost 5 times 0.2 because of adults, but this rate easily can be twice or even be triple value in commercial farms). Likewise, a dimensional analysis will be needed in the parameter definition.

Additonaly, the samplig strategy used would be better explained in a figure.

It is necessary to mention that the model is a set of differential equations.

Running time should be mentioned to reach endemic conditions or at least mention the time when reported results were obtained.

Reviewer #2: -Are the objectives of the study clearly articulated with a clear testable hypothesis stated?

Yes.

-Is the study design appropriate to address the stated objectives?

Yes, given limitations and assumptions have been stated clearly (which they have).

-Is the population clearly described and appropriate for the hypothesis being tested?

Yes.

-Is the sample size sufficient to ensure adequate power to address the hypothesis being tested?

The data used in this study have been previously published.

-Were correct statistical analysis used to support conclusions?

Yes, to the best of my knowledge.

-Are there concerns about ethical or regulatory requirements being met?

No.

Reviewer #3: The methods are generally clearly outlined and suitable for the research questions outlined. I do have some important questions/points that require clarification (see comments).

--------------------

Results

-Does the analysis presented match the analysis plan?

-Are the results clearly and completely presented?

-Are the figures (Tables, Images) of sufficient quality for clarity?

Reviewer #1: They are clear and completely presented, but they have to be confirmed after parameter corrections.

Reviewer #2: -Does the analysis presented match the analysis plan?

Yes

-Are the results clearly and completely presented?

Yes – with a few amendments to be made.

-Are the figures (Tables, Images) of sufficient quality for clarity?

Yes – with a few amendments.

Further comments:

• Line 356 should refer to average prevalence of active human cysticercosis to align with Figure 2(a) label.

• Figure 2 is a nice illustration/comparison of modelled outputs compared to data. Consider changing the y-axis to percentages for readability (e.g. 0%, 5%, 10%, 15% instead of 0, 0.1, 0.15).

• Results are clearly presented including any clearly outlining assumptions made regarding interpretation of results.

• Figure 3 needs a legend to indicate which province is represented by blue, yellow and green estimates.

• Figure 5 caption does NOT align with the figure. E.g. looking at Figure 5A and the labels therein I would interpret this as: 5% reduction in exposure to T. solium cysticerci in combination with a 5 – 50% reduction in exposure to T. solium eggs. This is NOT what is written in the Figure 5 caption on lines 443 – 452. The same comment goes for Figures 5B, 5C and 5D.

From the discussion text I think that it is the figure 5 caption which is incorrect.

• How was the elimination threshold of less than one case per 1,000 population decided upon?

Reviewer #3: The analysis matches the objectives outlined in the introduction. See further comments for clarifications in the results section.

--------------------

Conclusions

-Are the conclusions supported by the data presented?

-Are the limitations of analysis clearly described?

-Do the authors discuss how these data can be helpful to advance our understanding of the topic under study?

-Is public health relevance addressed?

Reviewer #1: Is it possible to mention which pork-made dishes are prepared and why they could contain undercooked pork?

Reviewer #2: -Are the conclusions supported by the data presented?

Yes

-Are the limitations of analysis clearly described?

Yes

-Do the authors discuss how these data can be helpful to advance our understanding of the topic under study?

Yes

-Is public health relevance addressed?

Yes

Reviewer #3: The conclusions are generally well supported. This paper provides an important contribution in the area of T. solium research, and the authors explain how this advances our understanding in the field.

--------------------

Editorial and Data Presentation Modifications?

Use this section for editorial suggestions as well as relatively minor modifications of existing data that would enhance clarity. If the only modifications needed are minor and/or editorial, you may wish to recommend “Minor Revision” or “Accept”.

Reviewer #1: Minor modifications:

L44 and elsewhere, citations and references are after final sentence dot.

L201: mention that the model is a set of differential equations

L335 is Eq 7?

Reviewer #2: (No Response)

Reviewer #3: Table 1: It is not clear what ME is, could the authors please define this.

Table 1: What does Sp represent in the footing of Table 1 (line 133) – I think it refers to susceptible pigs as as per the model figure, but this has not been defined yet in the text.

Table 2: It would be easier for the reader if another column was made available in Table 2 to indicate the standardized monthly rate for parameter estimates.

In Figure 3, it would be useful to include a legend for colour of the points based on each province for quick reference (otherwise there is a need to constantly refer back to Fig 2 to check)

Line 335: this should refer to equation 7 for the likelihood equation

--------------------

Summary and General Comments

Use this section to provide overall comments, discuss strengths/weaknesses of the study, novelty, significance, general execution and scholarship. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. If requesting major revision, please articulate the new experiments that are needed.

Reviewer #1: The manuscript "Data-driven analyses of behavioral strategies to eliminate cysticercosis in sub-Saharan Africa" offers an interesting and innovative methodology to study disease dynamic interactions based on community data. The reported results offer sufficient evidence to implement feasible strategies at a taeniasis/cysticercosis control program for researchers and decision-makers. The data offered by authors probabbly is unique to estimate worthing information of epidemiological parameters.

Reviewer #2: This article presents a deterministic multi-host (humans and pigs) compartmental model for the transmission of different stages of the tapeworm Taenia solium in a closed population. The purpose of the study presented is to consider the impact of less resource intensive interventions focused on human behaviours to eliminate transmission as a public health problem. The authors point out the importance of utilising large field-based study data to inform such interventions.

Overall, I think this study is of public health relevance and is a good starting point to addressing the gaps in currently available models of taeniosis/cysticercosis and the impacts of interventions on elimination of the disease as a public health problem. I have detailed comments below which need to be addressed prior to the publication of this manuscript.

The authors refer to elimination and define it as less than one case per 1,000 population. My understanding would be that this refers to “elimination as a public health problem”, if this is the case the authors should clarify this within their article.

The article is lacking a clear and concise description of what the authors refer to as “taeniosis/cysticercosis” (note that in the author summary only ‘cysticercosis’ is referred to). This needs to be incorporated more clearly into the introduction to give readers a clear idea of the disease in question . E.g. incorporate a description of the parasite lifecycle and the link between taenoiosis and cysticercosis – this could be written description or inclusion of a figure such as the one here: https://www.cdc.gov/parasites/cysticercosis/biology.html

Some of this information is presented under the dynamic transmission model section, but it needs to be explained earlier in the article than this to ensure you don’t lose readers, for example by referring to parasite stages (eg proglottids) before explaining why those stages are important.

• General comment: at first mention of Taenia solium put in brackets (T. solium) before using abbreviation throughout. Do not assume the reader will know what the abbreviation stands for.

• Question from assumption on line 227: do the authors think it is it realistic to assume that susceptible and infected pigs were slaughtered at equal rates, or are infected pigs likely to show signs of illness and be culled earlier or removed from production?

• Thorough description of the transmission model. The authors provide a transparent description of assumptions made about model parameters and the way they have incorporated the impact of interventions on reducing transmission.

• Line 332: Comment on the limitation or impact the use of aggregate quantities may have on derived estimates and model outcomes?

• Line 335: typo, I assume the likelihood equation is actually Equation (7) on line 320?

Reviewer #3: My summary: This is an important paper that, as identified by the authors, contributes to filling an gap in the area of T. solium research (developing transmission models informed by field-data). The model also provides a novel contribution by robustly assessing the impact of non-pharmaceutical interventions, with most T. solium models to date focusing on pharmaceutical interventions. In terms of contribution to understanding prospects for control, the paper considers interventions which might be more feasible/sustainable in severely resourced endemic settings.

The approach adopted uses data from a detailed study in Burkina Faso (with pre-randomisation baseline prevalence data, adjusted for diagnostic performance in a latent class model). A Bayesian Melding model fitting approach samples key parameters including the rate of loss of viable eggs (which is an important parameter to elucidate as very minimal data is available), two transmission coefficients for human taeniosis and porcine cysticercosis, and the ratio of human contact rate with eggs with pig contact rate with eggs. After fitting, the contact rates are identified as higher in Nayala compared to the other two provinces, while the rate of loss of viable eggs is similar across settings. Reduction in exposure to T. solium eggs is presented as a more effective intervention, compared to reducing consumption of undercooked meat at reaching human active cysticercosis elimination thresholds.

The differences in modelled contact rates between provinces eloquently explain the different effectiveness of modelled interventions between provinces, supporting the observations of heterogeneous intervention effectiveness in the field trial conducted in Burkina Faso by the same group.

Overall, I very much like this manuscript and think it will be an important contribution. I do however has some important points to raise below.

Introduction:

Including data/text on burden of disease in the introduction paragraph 2 (lines 46-50) to help contextualize the clinical aspect for more general audiences.

Methods:

Table 1

If I am understanding the methodology correctly, the prevalence estimates provided in Table 1 as the adjusted prevalence estimates obtained from the Latent class model, which are then used for model fitting. If this is the case, highlighting in Table 1 that these are adjusted prevalence estimates (not unadjusted), would improve clarity.

Table 2

It is not clear to me how the slaughter rate for domestic pigs is calculated from the detail provided (and how the reference [24] Chembensofu et al. 2017 is used to inform this). Please could the authors clarify.

Equations and structure

Could the authors explain why a pre-patent compartment in pigs is omitted, where this duration (2- 3 months as demonstrated by Yoshino, 1933a,b)) is non-negligble compared to the relatively short life-span of pigs in endemic settings :

Yoshino K. Studies on the post-embryonal development of Taenia solium, Pt. i. J Med Assoc Formosa 1933a;32:139–41.

Yoshino K. Studies on the Postembryonal Development of Taenia solium. Part II. On the Youngest Form of Cysticercus cellulosae and on the Migratory Course of the Oncosphaera of Taenia solium within the Intermediate Host. J Med Assoc Formosa 1933b;32:1569-1586.

Could the authors explain their rationale behind not including heterogeneity in burden of porcine cysticercosis infection (e.g. low or high burden) which could influence the probability of infection for human taeniosis infection?

The force-of-infection equation for human taeniosis (equation 2) indicates that human contact rate with pork is assumed to be frequency-dependent. It would be useful to explicitly state this, and similarly for human or pig contact rates with contaminated soil, where equations 1 and 4 indicate density-dependent contact rates are assumed.

Could the authors clarify the assumption that pork consumed at home “ was always cooked at a temperature sufficient for killing parasites” on lines 244-245 compared to pork cooked in the market. Did they see this in their data/ study area?

I am not clear on the definition of seroreversion rate parameter (θ) on lines 280-281, and Table 2 - is this seroreversion from both human cysticercosis and human taeniasis seropositivity back to full susceptibility? Lines 280-281 makes me think this is only seroreversion from human cysticercosis? Please could the authors clarify.

Also, should θ be defined as the human recovery or infection loss rate (from true infection i.e IH2 to SH), as presumably the seroprevalence data is adjusted based on the diagnostic performance, so seroreversion can be interpreted as those who are truly reverting from infected status to susceptibility? I find the name of the parameter (the seroreversion rate) slightly confusing as the model captures true infection dynamics (not seropositivity)?

How are the interventions applied? Are they implemented as an instantaneous reduction in the rate of transmission by the factors mentioned on lines 301 and 308 and maintained throughout the duration of the intervention programme? Also, when is the modelled prevalence measured to assess the impact of the intervention – is this in line with the 18-month follow-up (post randomisation survey) indicated in ref [22]? This is not clear in the “Intervention approaches” section of the methods. There is a little text on modelling “pulse interventions” in the model limitations section (lines 502-503), however more information should be provided in the methods section.

SI Model equations

There appears to be an error in equation # 4 in the SI equation: should the addition term to dIpm/dt be εIP not εIPm?

It is not clear what the subscript j refers to in model fitting algorithm section (lines 317 – 325), presumably where the model was fitted to each province, j represents each province? If so, could this be explicitly written (i.e. “For each of the provinces (j), four..”

Could the authors provide justification for the assumption that the contact rate of pigs with eggs in the environment (χP) is always larger than the contact rate of humans with eggs in the environment/ with other taeniosis carriers (χF) or autoinfection (χA), given the parameter estimates outlined in line 340 for model fitting and the information outlined in Table 2?

Results:

I find the Figure 5 legend slightly confusing – is 5A not a 5% reduction in consumption rather than 20% in the legend text on line 444 for example?

Discussion:

This section is currently quite short, so there is space for expansion on some points. Specific questions include:

The authors mention the added value of this paper in presenting “field-driven force-of-infection” modelling. It would be useful if the authors could present in the manuscript the specific province-level FoI estimates calculated in the model at endemic equilibrium.

Do the authors have any idea why the modelled contact rates are higher in Nayala, while the pre-intervention prevalence is the highest in Boulkiemdé? Would it not expected that a higher baseline T. solium prevalence would be found in a setting with higher contact rates (Nayala)? The authors begin to elude to this in lines 477-480, but I think more discussion should be provided.

The rate of loss of viable eggs in the environment is an important parameter, where minimal data is available from field settings (most models relying on data from other Taenia species). In Figure 3, the authors find a similar rate of loss of viable eggs in environment in each province. Is this expected? perhaps the authors could discuss more about the similarity (or not) of environmental conditions across provinces which could lead to these findings.

In results, it is stated that "βE is a biological parameter that could be assumed to uniform across provinces", however the probability of viable infection upon contact (with infective material) may vary on the basis of whether pigs are exposed to smaller doses e.g. contacting eggs in the soil (lower probability) compared to higher doses e.g. consuming proglottids (higher probability). Santamaria et al. 2002 (ref below) indicate that the efficiency of establishment (proportion of viable cyst developing) is influenced by the dose (eggs consumed). Have the authors considered this?

Santamaria E, Plancarte A, de Aluja AS. The Experimental Infection of Pigs with Different Numbers of Taenia solium Eggs: Immune Response and Efficiency of Establishment. J Parasitol 2002;88:69.

--------------------

PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Lenin Ron Garrido

Reviewer #2: No

Reviewer #3: No

Figure Files:

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org.

Data Requirements:

Please note that, as a condition of publication, PLOS' data policy requires that you make available all data used to draw the conclusions outlined in your manuscript. Data must be deposited in an appropriate repository, included within the body of the manuscript, or uploaded as supporting information. This includes all numerical values that were used to generate graphs, histograms etc.. For an example see here: http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1001908#s5.

Reproducibility:

To enhance the reproducibility of your results, PLOS recommends that you deposit laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see https://journals.plos.org/plosntds/s/submission-guidelines#loc-methods

11 Dec 2020

Submitted filename: Response to Reviewers_PLOS NTDs Cysticercosis.docx

Click here for additional data file.

13 Jan 2021

Dear Dr. Carabin,

Thank you very much for submitting your manuscript "Data-driven analyses of behavioral strategies to eliminate cysticercosis in sub-Saharan Africa" for consideration at PLOS Neglected Tropical Diseases. As with all papers reviewed by the journal, your manuscript was reviewed by members of the editorial board and by several independent reviewers. The reviewers appreciated the attention to an important topic. Based on the reviews, we are likely to accept this manuscript for publication, providing that you modify the manuscript according to the review recommendations.

The reviewers acknowledged and were satisfied by the content and detail of your responses. We would like to see a few remaining and reasonable questions stemming from your responses addressed. We encourage you to address was many of the questions as you can, but particularly the query regarding point 28 requested by Reviewer #3, if possible.

Please prepare and submit your revised manuscript within 30 days. If you anticipate any delay, please let us know the expected resubmission date by replying to this email.

When you are ready to resubmit, please upload the following:

[1] A letter containing a detailed list of your responses to all review comments, and a description of the changes you have made in the manuscript.

Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out

[2] Two versions of the revised manuscript: one with either highlights or tracked changes denoting where the text has been changed; the other a clean version (uploaded as the manuscript file).

Important additional instructions are given below your reviewer comments.

Thank you again for your submission to our journal. We hope that our editorial process has been constructive so far, and we welcome your feedback at any time. Please don't hesitate to contact us if you have any questions or comments.

Sincerely,

Siddhartha Mahanty, M.B.B.S., M.P.H

Associate Editor

PLOS Neglected Tropical Diseases

Marco Coral-Almeida

Deputy Editor

PLOS Neglected Tropical Diseases

***********************

Reviewer's Responses to Questions

Key Review Criteria Required for Acceptance?

As you describe the new analyses required for acceptance, please consider the following:

Methods

-Are the objectives of the study clearly articulated with a clear testable hypothesis stated?

-Is the study design appropriate to address the stated objectives?

-Is the population clearly described and appropriate for the hypothesis being tested?

-Is the sample size sufficient to ensure adequate power to address the hypothesis being tested?

-Were correct statistical analysis used to support conclusions?

-Are there concerns about ethical or regulatory requirements being met?

Reviewer #1: The new version of the article has incorporated important recommendations suggested for the previous version. I think methodological observations were taken into account and they were addressed correctly. Maybe the software used to run the analysis should be mentioned in the Methodology. Consequently, I consider that the stated questions were properly answered and therefore, the article must be accepted.

Reviewer #2: (No Response)

Reviewer #3: (No Response)

--------------------

Results

-Does the analysis presented match the analysis plan?

-Are the results clearly and completely presented?

-Are the figures (Tables, Images) of sufficient quality for clarity?

Reviewer #1: Results offer important insights for the human Taeniasis-cysticercosis control at the community level. The model captures the general Taeniasis-cysticercosis community dynamics and its parameter estimates seem adequate in the transmission dynamics.

Reviewer #2: (No Response)

Reviewer #3: (No Response)

--------------------

Conclusions

-Are the conclusions supported by the data presented?

-Are the limitations of analysis clearly described?

-Do the authors discuss how these data can be helpful to advance our understanding of the topic under study?

-Is public health relevance addressed?

Reviewer #1: The conclusion presented by the authors in the manuscript reflects clearly what they were looking for in the objectives of this research. It also gives important insights for control strategies against the Taeniasis -cysticercosis disease complex, therefore it is of public health relevance.

Reviewer #2: (No Response)

Reviewer #3: (No Response)

--------------------

Editorial and Data Presentation Modifications?

Use this section for editorial suggestions as well as relatively minor modifications of existing data that would enhance clarity. If the only modifications needed are minor and/or editorial, you may wish to recommend “Minor Revision” or “Accept”.

Reviewer #1: Authors properly have managed the questions related to the estimation of epidemiological parameters and therefore, I think, the model may be a useful tool with proper parameter values necessary to understand this disease dynamics and to manage strategies for disease control and elimination in the communities. Therefore I recommend accepting it to publish in PLOS NTD. I have suggested just to include the software used for the model running.

Reviewer #2: (No Response)

Reviewer #3: (No Response)

--------------------

Summary and General Comments

Use this section to provide overall comments, discuss strengths/weaknesses of the study, novelty, significance, general execution and scholarship. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. If requesting major revision, please articulate the new experiments that are needed.

Reviewer #1: The manuscript "Data-driven analyses of behavioral strategies to eliminate cysticercosis in sub-Saharan Africa" provides important epidemiological parameters useful to model the epidemy dynamics and to predict the disease behavior with control tools for this disease complex. The model suggests that the use of suitable tools at the community level may help control the problem and gives insights about the period and necessary efforts to reduce the burden of the disease. The authors have properly have discussed the drawbacks of this kind of modeling, and have described the main model limitations. In spite of this, model conclusions result epidemiologically relevant.

Reviewer #2: By revising this manuscript and addressing concerns highlighted by the reviewers in detail, the authors have produced an interesting manuscript of public health relevance which is now fit for publication.

Reviewer #3: Firstly, I would like to thank the authors on their detailed responses, and congratulate the authors on an improved manuscript. Before proceeding, I would like to first request clarification on the following responses please:

In response to point 27:

Thank you for further clarification on the slaughter rate, this is much clearer now. Could the authors walk me through their derivation of 12;14;74% dying for the three different reasons mentioned in the supplementary paragraph below:

"Among all pigs alive at any point in time, 74% are pigs who will survive to slaughter. This is based on the following: among 7 piglets born per sowyear (based on local expertise (Ganaba), we assume that in the rural setting each sow of reproductive age farrows once per year and the number of piglets is based on ref [29]), 50% will die before weaning at age 0.17 years (based on ref [29] and our data), 20% will die at age 0.5 years between weaning and slaughter (death rate in this period is not available but assumed from the age distribution of pigs alive at the time of our surveys), and 30% will survive to slaughter (including sows kept for reproduction) corresponding to 12%, 14% and 74% of piglets dying before weaning, dying between weaning and

slaughter and being slaughtered (including sows kept for reproduction)."

In response to point 28:

If I am understanding correctly, does this not indicate that non-infected pigs largely become resistant after age of 3 months (with continued exposure), if (age-?)prevalence does not increase from 40% after 3-months of age (assuming constant exposure with age)? As this is not an age-structured model or does not include parameters for immunity, the authors will not be able to plot an age-prevalence curve to see if the model captures these age-infection dynamics. However, the model presented without age-structuring here presumably models a constant force-of-infection with respect to age, therefore the prevalence will increase with age. I want to authors to comment on this, given they mention in the manuscript the prevalence doesn’t rise from 3 months of age and their model will not presumably capture their own field observations (of prevalence saturating with age; therefore the current model assumes prevalence keeps increasing with age, so slaughter age-animals will have a higher prevalence than those at 3-months of age), and have not included parameters for immunity (which may lead to an underestimation in the force-of-infection). See Lewis and Torgerson 2014 (Echinoccocus multilocularis), and Torgerson et al 1998 (Taenia hydatigena) which use a simpler catalytic model formulation fitted to age-prevalence curves for further reference.

- Lewis, F.I., Otero-Abad, B., Hegglin, D., Deplazes, P. and Torgerson, P.R., 2014. Dynamics of the force of infection: insights from Echinococcus multilocularis infection in foxes. PLoS neglected tropical diseases, 8(3) e2731.

- Torgerson, P.R., Williams, D.H. and Abo-Shehada, M.N., 1998. Modelling the prevalence of Echinococcus and Taenia species in small ruminants of different ages in northern Jordan. Veterinary Parasitology, 79(1), pp.35-51.

In response to points 32 & 33:

I still find this this a little unclear- as the authors response suggest, can they authors remove the “from seropositivity” and “(seroreversion) in the “Recovery from seropositivity after loss of cysticercosis infection (seroreversion)” for parameter θ in table 2, and similarly on line 313 of the revised manuscript, removing “seroreversion”.

In response to point 34:

With the intervention simulations run to equilibrium, can the authors state the timeframe(s) to reach equilibrium under the different intervention strategies (is there significant variation for example if I am understanding correctly)? Are these within a realistic timeframe (i.e. if the simulations have taken a significant time to reach equilibrium, is it realistic that interventions/behaviour changes would be maintained for so long)?

Additional comment:

Will model code be available upon publication, which will be important for transparency (for example, see other published Taenia solium transmission models, CystiSim and EPICYST which both have code available through GitHub).

--------------------

PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

Figure Files:

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org.

Data Requirements:

Please note that, as a condition of publication, PLOS' data policy requires that you make available all data used to draw the conclusions outlined in your manuscript. Data must be deposited in an appropriate repository, included within the body of the manuscript, or uploaded as supporting information. This includes all numerical values that were used to generate graphs, histograms etc.. For an example see here: http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1001908#s5.

Reproducibility:

To enhance the reproducibility of your results, PLOS recommends that you deposit laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see http://journals.plos.org/plosntds/s/submission-guidelines#loc-materials-and-methods

31 Jan 2021

Submitted filename: Cysticercosis_PLOS NTDs_Response to Reviewers v2_FNL.docx

Click here for additional data file.

10 Feb 2021

Dear Dr. Carabin,

We are pleased to inform you that your manuscript 'Data-driven analyses of behavioral strategies to eliminate cysticercosis in sub-Saharan Africa' has been provisionally accepted for publication in PLOS Neglected Tropical Diseases.

Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. A member of our team will be in touch with a set of requests.

Please note that your manuscript will not be scheduled for publication until you have made the required changes, so a swift response is appreciated.

IMPORTANT: The editorial review process is now complete. PLOS will only permit corrections to spelling, formatting or significant scientific errors from this point onwards. Requests for major changes, or any which affect the scientific understanding of your work, will cause delays to the publication date of your manuscript.

Should you, your institution's press office or the journal office choose to press release your paper, you will automatically be opted out of early publication. We ask that you notify us now if you or your institution is planning to press release the article. All press must be co-ordinated with PLOS.

Thank you again for supporting Open Access publishing; we are looking forward to publishing your work in PLOS Neglected Tropical Diseases.

Best regards,

Siddhartha Mahanty, M.B.B.S., M.P.H

Associate Editor

PLOS Neglected Tropical Diseases

Marco Coral-Almeida

Deputy Editor

PLOS Neglected Tropical Diseases

***********************************************************

17 Mar 2021

Dear Dr. Carabin,

We are delighted to inform you that your manuscript, "Data-driven analyses of behavioral strategies to eliminate cysticercosis in sub-Saharan Africa," has been formally accepted for publication in PLOS Neglected Tropical Diseases.

We have now passed your article onto the PLOS Production Department who will complete the rest of the publication process. All authors will receive a confirmation email upon publication.

The corresponding author will soon be receiving a typeset proof for review, to ensure errors have not been introduced during production. Please review the PDF proof of your manuscript carefully, as this is the last chance to correct any scientific or type-setting errors. Please note that major changes, or those which affect the scientific understanding of the work, will likely cause delays to the publication date of your manuscript. Note: Proofs for Front Matter articles (Editorial, Viewpoint, Symposium, Review, etc...) are generated on a different schedule and may not be made available as quickly.

Soon after your final files are uploaded, the early version of your manuscript will be published online unless you opted out of this process. The date of the early version will be your article's publication date. The final article will be published to the same URL, and all versions of the paper will be accessible to readers.

Thank you again for supporting open-access publishing; we are looking forward to publishing your work in PLOS Neglected Tropical Diseases.

Best regards,

Shaden Kamhawi

co-Editor-in-Chief

PLOS Neglected Tropical Diseases

Paul Brindley

co-Editor-in-Chief

PLOS Neglected Tropical Diseases