Schistosomiasis is a parasitic neglected tropical disease of considerable public health importance. Schistosomiasis affects approximately 240 million people worldwide (1), causing chronic and acute morbidity, including anemia, wasting, and damage to intestinal or urogenital systems. The global burden of schistosomiasis was estimated in 2021 at 1.75 (95% uncertainty interval [UI] 1.04–2.99) million disability adjusted life years, with 12,900 deaths (95% UI 11,400–14,700), the majority of which occurred in sub-Saharan Africa (2). The World Health Organization (WHO) has targeted schistosomiasis for elimination as a public health problem (<1% prevalence of heavy-intensity infections) by 2030, principally using a strategy of annual or semi-annual mass drug administration (MDA) with praziquantel (1).

Schistosomes are transmitted indirectly via intermediate freshwater snail hosts; consequently, exposure is linked to contact with water bodies containing infectious cercarial larvae. Five decades ago, Warren (3) first noted the difficulty of distinguishing the contributions of “immunology or ecology” to the convex age-intensity profiles of schistosome infections (4). Repeated exposure may promote a partially protective immune response, causing peak infection intensity to occur in earlier childhood in areas of intense transmission due to the more rapid acquisition of immunity (“peak shift”) (5–8). However, childhood peaks in infection intensity are also likely driven by age-dependent contact rates with contaminated water bodies, which are often greater in children than adults (9, 10). Hence, the relative importance of acquired immunity (“immunology”) vs. exposure (“ecology”) to the epidemiology of schistosomiasis has remained elusive.

Resolving the contributions of immunity and exposure is critical for understanding the transmission dynamics of schistosomiasis and for modeling responses to interventions. Protective immunity increases the resilience of helminthiases to intervention, making it more difficult to achieve elimination targets (9, 11). Recent advances have indicated that immunoglobulin E (IgE) responses against Tegumental-Allergen-Like (TAL) proteins are likely a major component of so-called “delayed concomitant immunity” (12). By this proposed mechanism, protective immunological responses are mediated by the death of adult schistosomes which induce antibodies that are cross-reactive with TAL proteins present on invading cercariae (12, 13). Delayed concomitant immunity may also provide a strong passive vaccination effect following praziquantel treatment of heavily infected individuals, initially boosting immunity and enhancing protection against reinfection (14), but waning following subsequent treatments.

In recent years, schistosomiasis transmission models have been increasingly used for public health decision-making, including on the frequency and population coverage of MDA required to achieve the 2030 elimination goals (reviewed previously (15)). However, due to uncertainty on the relative contributions of exposure vs. immunity, these models have typically attributed age-infection patterns exclusively to exposure (e.g. (16), although see also Refs. (9–11, 17, 18)). Depending on the nature and strength of acquired immunity, this assumption may make current projections on the long-term effectiveness of MDA too optimistic. Improved understanding of acquired immunity in natural populations would also benefit the development of effective schistosomiasis vaccines (19, 20).

Here, we develop a novel mathematical transmission model to resolve the contributions of exposure and acquired immunity to the epidemiology of intestinal schistosomiasis using a unique immunoepidemiological dataset collected from 110 individuals aged between 7 and 50 years living on the shores of Lake Albert, Uganda, before the initiation of MDA (21, 22). We use data on water contact and malacological surveys (23, 24) to infer age- and sex-dependent patterns of cercarial exposure and estimate the protective effect of delayed concomitant immunity using individual-level parasitological data on infection intensity and immunological data on Schistosoma mansoni Tegumental-Allergen-Like protein 1 (SmTAL1) IgE antibodies. We compare model variants with and without protective acquired immunity to determine its importance in capturing observed immunoepidemiological profiles. We also explore how immunity affects transmission dynamics during MDA. We discuss our findings in the context of the longstanding debate on schistosome exposure vs. immunity and the broader immunoepidemiology of schistosomiasis.

Cercarial exposure shows a similar convex-like pattern in males and females, peaking at 11 and 15 years, respectively, before gradually declining throughout adulthood (Fig. 1). The fit of the transmission model (Fig. 2) to preintervention immunoepidemiological data is shown in Fig. 3A and B (“Baseline”) for the model variant without protective immunity (“standard model”) and with protective immunity (“immunity model”). The immunity model shows a sharper peak in infection intensity (eggs per gram of feces [epg]) in school-aged children (SAC) and a steeper decline into older ages than the standard model (Fig. 3A, “Baseline”; see Fig. S2 for an overlaid plot). Accordingly, in older ages the rate of increase in SmTAL1-IgE optical density (OD) is lower for the immunity model than for the standard model (Fig. 3B, “Baseline”). The deviance information criterion (DIC) indicates the standard model to be a more parsimonious and adequate fit to the data than the more complex immunity model (standard model 50.94 [95% credible interval, crI, 50.67–51.44] and immunity model 51.12 [95% crI 50.73–51.59]).

Parameter posterior distributions from each model are summarized in Fig. 4 (see also Figs. S3 and S4, Figs. S5 and S6 for pairwise correlations, and Fig. S7 for posterior log likelihoods). The median SmTAL1-IgE half-life (12 ln(2)/σ, where σ is the rate of loss; Fig. 4) is 1.1 months for both models, with 95% crI of 1.0–1.6 months for the standard model and 1.0–1.5 months for the immunity model. For the immunity model, the strength of protection against cercarial infection establishment is highly uncertain (ω, posterior distribution uniform over prior range; Figs. 4 and S4) despite mild and statistically nonsignificant pairwise correlations with other fitted parameters (correlation coefficient range −0.15 to 0.11, Fig. S6). Some resolution was obtained for the human-to-snail population density parameter (N₁/N₂, greater posterior vs. prior densities for values over ∼0.3; Figs. 4, S3, and S4), but other parameter posterior estimates were largely indistinguishable from priors (Fig. 4).

Both model variants show good predictive performance against epg and SmTAL1-IgE OD values collected at 5 weeks (Fig. 3A and B, “5 weeks”) after praziquantel treatment and against epg collected additionally at 12 months (Fig. 3A, “12 months”), and 18 months (Fig. 3A, “18 months”) post-treatment (note that SmTAL1-IgE was only measured up to 5 weeks after treatment) (24). There was no difference in model performance by root mean squared error (RMSE) in capturing post-treatment epg (standard model, 255 [95% crI 47.3–617]; immunity model, 260 [95% crI 47.7–628]) or SmTAL1-IgE (standard model, 0.24 [95% crI 0.18–0.34]; immunity model, 0.23 [95% crI 0.17–0.32]) (Fig. S8).The long-term epg dynamics through 10 rounds of annual MDA—assuming 75% coverage of SAC (1) and a nominal 30% of adults (≥16 years old), yielding a mean coverage of 50.5% in line with Ugandan coverage surveys (26, 27)—are consistently lower for the immunity model compared to the standard model (Fig. 3C, “epg”), likely since infection intensities are more concentrated in SAC in the former (Fig. 3A, “Baseline”). SmTAL1-IgE OD dynamics are similar in both models until approximately 5 years after MDA initiation, after which antibodies decline faster in the immunity model (Fig. 3C, “SmTAL1-IgE (OD)”), reflecting a lower antigenic stimulus from lowered worm burdens (and, consequently, epg; Fig. 3C). For both models, SmTAL1-IgE ODs fall below preintervention levels (Fig. 3C). The immunity model projections are associated with wide uncertainty intervals, particularly for epg (Fig. 3C), reflecting uncertainty in both preintervention fits (chiefly in SAC; Fig. 3A, “Baseline”) and the strength of protection afforded by SmTAL1-IgEs (ω, Fig. 4). This translates into more uncertain prevalence dynamics for the immunity model, further compounded by uncertainty in the among-host worm overdispersion parameter (k, used to calculate prevalence; Fig. S9). Some immunity model simulations initially show stark epg decreases which thereafter remain persistently low (Fig. 3C “epg,” immunity model lower 95% crI). These are associated with low values of basic reproduction number (R0), human-to-snail population density (N₁/N₂), SmTAL1-IgE decay (σ), and immune constant (ϕ), and high values of immune protection (ω) (Fig. S10).

The relative importance of age-dependent exposure vs. acquired immunity to typical convex age-intensity profiles is a major unresolved question in schistosomiasis epidemiology (3, 9–11, 30). Understanding the relative contributions of these two processes has important implications for transmission dynamics, responses to MDA, including the feasibility of achieving the WHO 2030 goals (1). Here, we have used a unique immunoepidemiological dataset (24)—which includes individual data on exposure to infectious cercariae (23)—combined with a mathematical transmission model to attempt to resolve the effects of delayed concomitant immunity and age-dependent exposure on the epidemiology of intestinal schistosomiasis in a highly endemic region of western Uganda. We found that the model variants incorporating or omitting acquired immunity captured equally well observed age profiles of infection intensity and SmTAL1-IgE antibodies before and up to 18 months after praziquantel treatment. It therefore appears that delayed concomitant immunity is not required to adequately describe the transmission of intestinal schistosomiasis in this highly endemic epidemiological setting and its protective effect is highly uncertain. However, we also stress that we have taken a conservative approach to parameter inference, that the protective effects of immunity may only become apparent over longer time horizons in populations subject to MDA, and that the proxy of immunity used is a necessary simplification of the proposed delayed concomitant mechanism (12). We also emphasize that these conclusions are based on findings from a single highly endemic setting, using data from 110 individuals. It is conceivable that a larger sample size would be required to detect acquired immunity if its effects are relatively weak. Therefore, acquired immunity should not be entirely discounted from future modeling efforts aimed at projecting the effectiveness of interventions.

Many previous mathematical modeling studies have considered the role of acquired immunity on the epidemiology of schistosomiasis, but these have generally focused on the theoretical implications of immunity for control and elimination efforts (9–11, 18). While some models have been calibrated against exposure and infection data (9–11), data have typically been lacking on antibody responses, limiting inference on the role of immunity (3). The key novelty of our study is the use of individual data on exposure, infection, and immunological responses which permits, in principle, the relative contributions of exposure and immunity to be disaggregated. We focused on delayed concomitant immunity (as opposed to other postulated mechanisms of acquired immunity (31)) to align with the available immunological data on SmTAL1-IgEs which comprise the primary antibody response following the death of adult worms (13, 14, 17, 32–35) and which have been previously associated with reduced rates of reinfection (e.g. (36) and references therein). Notwithstanding, SmTAL1-IgE is a proxy for a proposed immunity-generating process acting via TAL family members such as SmTAL3, SmTAL5, and SmTAL11, since SmTAL3/SmTAL5/SmTAL11 responders are known to be a subset of SmTAL1 responders (12, 13, 37). SmTAL3 and SmTAL11 are expressed predominantly in adult worms, and IgE specific to these antigens is cross-reactive with SmTAL5 (13) expressed on cercariae and early schistosomulae. Hence, while immunity is stimulated by worm death (i.e. “delayed”), the protective response is thought to be protective against invading stages (i.e. “concomitant”).

We found that most model parameters were only weakly identifiable from the data, such that many different parameter combinations could yield similar immunoepidemiological patterns that adequately captured the data. We deliberately chose a conservative approach to parameter inference by assigning vague priors to all unknown parameters and avoided harder assumptions associated with fixing values to uncertain model parameters. While this avoids potential bias, it also highlights the limitations and challenges of parameter inference using transmission models with multiple unknown or highly uncertain parameters (38). The data were most informative on the half-life of SmTAL1-IgE antibodies, with both model variants yielding a central estimate of 1.1 months and an uncertainty range of 1–1.6 months. Without replacement, IgE has a circulating half-life of 2 days, and a half-life in the skin, the proposed site of parasite killing, of 16–20 days (39). The half-life of IgE secreting plasma cells—which replace circulating IgE—is more contentious, spanning from months to years. Blockage of plasma cell production with the immunotherapeutic drug Dupilumab shows >80% loss of circulating IgE over 1 year (reviewed in Ref. (40)), a slower kinetic than found here. While no other studies have examined SmTAL1-IgE half-life, previous unpublished work found significantly lower titers of schistosome worm antigen-specific IgE 1 year after treatment of Kenyan SAC (37). Further, S. haematobium models developed to investigate antibody isotype switching (32, 33) estimated an initial antibody response from short-lived plasma cells of 5–46 days (33) and 3.2–32 days (32), while estimates of the longer-lived antibody response were 9–90 years (33) and 10 months–87 years (32). The difference in estimates between previous work and ours could reflect biological differences between schistosome species, the modeled mechanism of protective immunity, and other modeling assumptions (e.g. age-exposure patterns and worm life-span). While we do not find that delayed concomitant immunity is necessary to explain immunoepidemiological profiles at endemic equilibrium and 18 months post-treatment in this population, we cannot rule out its importance for the longer-term epidemiology and transmission dynamics of intestinal schistosomiasis.

A principle of helminth epidemiology is that acquired immunity increases the resilience of parasite populations to interventions via the release of immune-mediated density-dependent constraints (11, 41). Previous transmission dynamics modeling of schistosomiasis has demonstrated this explicitly, showing that the loss of acquired immunity during MDA increases rates of reinfection (9, 18). By contrast, our modeling of MDA shows that stronger declines in infection and decreased rates of reinfection occur when immunity is incorporated compared to when it is omitted. This occurs because of the protection against reinfection afforded by SmTAL1-IgE antibodies—which are transiently boosted following the death of adult schistosomes after treatment—but also because the accumulation of protective antibodies during childhood increases the aggregation of worms in SAC, the demographic with the highest coverage of MDA.

Past models have often assumed that cumulative live worms are the source of antigenic stimulation for acquired immunity against schistosomes (9, 11, 18) but a compelling body of evidence now suggests this role is instead fulfilled by cumulative exposure to dying worms (12–14, 17, 32–34). These different sources of immunostimulation will yield tangible differences in projected dynamics. Assuming a live-worm stimulus, reductions in worm burden caused by treatment will cause a faster decline in protective immunity leading to more rapid rates of reinfection (18). Assuming dead worms provide the stimulus, worms killed by treatment will boost the immune response, initially reducing rates of reinfection. However, in keeping with previous serological (42, 43) and modeling (17) studies, our model also highlights that the immunological boosting effect of praziquantel is transient, both immediately after treatment—due to the relatively short estimated half-life of SmTAL1-IgE—and longer-term due to reductions in infection. Thus, in the long term, the qualitative effect on transmission dynamics of different sources of immunostimulation will become similar as population immunity is diminished under both mechanisms. Indeed, premature cessation of MDA can result in a rapid rebound in infections, even “overshooting” pretreatment levels (17, 44).

Our approach to modeling delayed concomitant immunity is necessarily a simplification of the underlying immunological mechanisms and incurs limitations. First, it is possible that our strategy of leveraging the relationship between SmTAL1 and SmTAL3/5 gave insufficient resolution to detect an immune effect. Previous work from Lake Victoria, Uganda, found that of 89 individuals with measureable SmTAL1-IgE titers, only 43% (n = 38) were SmTAL3-IgE responders, and 19% (n = 17) SmTAL5-IgE responders (13, 37). If these proportions were similar for our dataset, it might be challenging to find a protective signal—particularly if it were weak. Second, we do not account for a possible counter-balancing effect of IgG4, which is thought to downregulate IgE by competitively binding to the same epitopes (45). Several studies have reported that the balance of IgE/IgG4 determines the resistance vs. susceptibility to reinfection (24, 45, 46). Finally, we use a deterministic model which gives a mean-field approximation of transmission dynamics. A stochastic individual-based model would permit individual variability in worm burdens and antibody responses to be captured; albeit this approach would incur considerable technical difficulties in fitting to data. Notwithstanding these limitations, we emphasize the significant utility of the modeling framework presented here, which could be adapted to fit other data or other proposed immune mechanisms.

Future research could seek to design alternative population sampling strategies to better distinguish the two hypotheses represented by the model variants. Since datasets on long-term TAL family IgE dynamics are lacking, it would be helpful to introduce longer-term immunological monitoring of endemic populations. Data collected from such monitoring could then be used in conjunction with longer-term longitudinally collected parasitological data—such as programmatic data collected during MDA—to better validate and compare the long-term model dynamics. Future modeling studies could also focus on other markers of acquired immunity, including the newly characterized SmTAL11, which has also been implicated in the generation of cross-reactive IgEs specific to SmTAL3 and SmTAL5 (12).

In conclusion, the contributions of exposure vs. immunity to schistosome epidemiology, first noted five decades ago (3), remain unresolved. This article illustrates that disentangling these two processes is challenging even with complete individual-level immunoepidemiological data. We found that model variants incorporating or omitting delayed concomitant immunity could describe equally well immunoepidemiological patterns of intestinal schistosomiasis before intervention and 18 months after MDA in a highly endemic community of western Uganda. Despite this unresolved uncertainty, our modeling also indicates that the effects of acquired immunity may become apparent after repeated years of MDA and thus immunity should not be discounted from future modeling projections on the effectiveness of schistosomiasis interventions and the feasibility of reaching the WHO 2030 elimination goals.