Understanding West Nile virus transmission: Mathematical modelling to quantify the most critical parameters to predict infection dynamics

Seroprevalence of West Nile Virus among Equids in Bulgaria in 2022 and Assessment of Some Risk Factors

The aim of this study was to analyze the seroprevalence of West Nile virus (WNV) among equids in Bulgaria, confirm the results of a competitive ELISA versus the virus neutralization test (VNT) and investigate some predisposing factors for WNV seropositivity. A total of 378 serum samples from 15 provinces in northern and southern Bulgaria were tested. The samples originated from 314 horses and 64 donkeys, 135 males and 243 females, aged from 1 to 30 years. IgG and IgM antibodies against WNV protein E were detected by ELISA. ELISA-positive samples were additionally tested via VNT for WNV and Usutu virus. Thirty-five samples were WNV-positive by ELISA (9.26% [CI = 6.45-12.88]), of which 15 were confirmed by VNT; hence, the seroprevalence was 3.97% (CI = 2.22-6.55). No virus-neutralizing antibodies to Usutu virus were detected among the 35 WNV-ELISA-positive equids in Bulgaria. When compared with VNT, ELISA showed 100.0% sensitivity and 94.5% specificity. A statistical analysis showed that the risk factors associated with WNV seropositivity were the region (p < 0.0001), altitude of the locality (p < 0.0001), type of housing (p < 0.0001) and breed (p = 0.0365). The results of the study demonstrate, albeit indirectly, that WNV circulates among equids in northern and southern Bulgaria, indicating that they could be suitable sentinel animals for predicting human cases and determining the risk in these areas or regions of the country.

Mechanistic models for West Nile virus transmission: a systematic review of features, aims and parametrization

Mathematical models within the Ross-Macdonald framework increasingly play a role in our understanding of vector-borne disease dynamics and as tools for assessing scenarios to respond to emerging threats. These threats are typically characterized by a high degree of heterogeneity, introducing a range of possible complexities in models and challenges to maintain the link with empirical evidence. We systematically identified and analysed a total of 77 published papers presenting compartmental West Nile virus (WNV) models that use parameter values derived from empirical studies. Using a set of 15 criteria, we measured the dissimilarity compared with the Ross-Macdonald framework. We also retrieved the purpose and type of models and traced the empirical sources of their parameters. Our review highlights the increasing refinements in WNV models. Models for prediction included the highest number of refinements. We found uneven distributions of refinements and of evidence for parameter values. We identified several challenges in parametrizing such increasingly complex models. For parameters common to most models, we also synthesize the empirical evidence for their values and ranges. The study highlights the potential to improve the quality of WNV models and their applicability for policy by establishing closer collaboration between mathematical modelling and empirical work.

Risk of a vector-borne endemic zoonosis for wildlife: Hosts, large-scale geography, and diversity of vector-host interactions for Trypanosoma cruzi

Drivers for wildlife infection are multiple and complex, particularly for vector-borne diseases. Here, we studied the role of host competence, geographic area provenance, and diversity of vector-host interactions as drivers of wild mammal infection risk to Trypanosoma cruzi, the aetiological agent of Chagas disease. We performed a systematic sampling of wild mammals in 11 states of Mexico, from 2017 to 2018. We tested the positivity of T. cruzi with the Tc24 marker in tissues samples for 61 wild mammal species (524 specimens sampled). 26 mammal species were positive for T. cruzi, of which 11 are new hosts recorded in Mexico 75 specimens were positive and 449 were negative for T. cruzi infection, yielding an overall prevalence of 14.3%. The standardized infection risk of T. cruzi of our examined specimens was similar, no matter the host species or their geographic origins. Additionally, we used published data of mammal positives for T. cruzi to complement records of T. cruzi infection in wild mammals and inferred a trophic network of Triatoma spp. (vectors) and wild mammal species in Mexico, using spatial data-mining modelling. Infection with T. cruzi was not homogeneously distributed in the inferred trophic network. This information allowed us to develop a predictive model for T. cruzi infection risk for wild mammals in Mexico, considering risk as a function of the diversity of vector-host spatial associations in a large-scale geographic context, finding that the addition of competent vectors to a multi-host parasite system amplifies host infection risk. The diversity of vector-host interactions per se constitutes a relevant driver of infection risk because hosts and vectors are not isolated from each other.