The on-going African swine fever pandemic has been devastating to affected nations, with continued spread observed despite aggressive interventions. Suspected interspecific transmission among wild and domestic hosts further complicates control efforts, yet its role in epidemic propagation remains poorly understood. Here, we develop and calibrate a multi-host mechanistic transmission model to the first wave of the epidemic in Romania (June-December 2018), quantifying these dynamics and evaluating counterfactual management scenarios. We estimated that 60% (95% credible interval: 27-83%) of outbreak farms were linked to other outbreak farms, 27% (5.3-67%) to infected wild boar populations, and 13% (1.9-27%) to external sources. For wild boar, 39% (3.8-93%) of infected populations were estimated to have originated from outbreak farms, and 61% (7.3-96%) from other infected wild boar populations, with favorable habitat exhibiting higher susceptibility and infectivity than unfavorable habitat. Among alternative control strategies, reactive and preventive culling of domestic pig herds yielded the greatest decrease in median final epidemic size among domestic pigs. These findings provide quantitative evidence that interspecific transmission was a critical epidemic driver, and a necessary target for achieving holistic control. Our model offers a flexible, rapidly-deployable framework for informing surveillance and response policy in at-risk regions.

Introduction:The recurring epizootics of highly pathogenic avian influenza (HPAI) in France have been associated with changes in the epidemiological landscape, such as higher frequency of detections in wild birds and introductions into backyard farms. This highlights the need for a deeper understanding of the factors that drive the spread of HPAI, particularly environmental ones, which, unlike other factors, are still understudied. Methods:In this study, we examined various farm and environmental variables around the 2022-2023 outbreak sites in France to unravel potential common traits among detected outbreaks. From August 2022 to March 2023, 397 poultry farms were infected, including different species and production types. For each outbreak, the farm characteristics and variables related with their direct environment within a 2 km radius were collected. Based on the Gower distance, accounting for qualitative and quantitative variable, clusters were identified using k-medoid partitioning algorithm. A random forest analysis was further used to hierarchize the relative role of each variable in the clustering process, to assess the importance of the farm structural and environmental conditions on the outbreak occurrence. To disentangle the impact of environmental factors from intrinsic herd characteristics, the method was applied twice: first, using the whole dataset including the farm characteristics and environmental variables (first scenario); second, accounting exclusively for the environmental variables (second scenario). Results:Overall, farm variables such as farm type were crucial in the clustering process, overpassing most of the environmental factors, although the distance from "particular risk zones" and the coastline were also important. However, the clusters obtained with the second scenario that counts only for the environmental variables, remained consistent with the first scenario. Discussion:This shows a non-negligible impact of environmental conditions on the probability of viral introduction in poultry herds. This study used an innovative approach to explore how HPAI dynamics can be influenced by external factors, which could help in the design of risk zones at the national level.

Foodborne transmission appears to be a significant route for human hepatitis E virus (HEV) infection in Europe. We have developed a quantitative microbiological risk assessment (QMRA) for HEV infection due to consumption of three selected pork products (liver pâté, minced meat, and sliced liver), which models the steps from farm to human consumption in high detail, including within‐farm transmission dynamics and microbiological processes such as cross contamination and thermal inactivation. Our model is unique in that it considers prevalence and viral load of two microbiological variables, HEV RNA and infectious HEV, expressing the latter in terms of the former through so‐called “adjustment factors” where data are lacking. When the QMRA was parameterized for France and using infectious HEV, we found that sliced liver posed by far the highest risk of infection, with mean probability per portion , corresponding to human cases annually. For minced meat, the probability of infection was , with only human cases. While our model predicted appreciable levels of HEV RNA remaining in liver pâté at the point of consumption, the amount of infectious HEV and hence risk of infection was zero, emphasizing the importance of using the correct microbiological variable when assessing the risk to consumers. Owing to its highly mechanistic nature, our QMRA can be used in future work to assess the impact of control measures along the pork‐supply chain at high resolution.

Animal mobility is central to pastoral livelihoods and regional trade in West Africa, but it also facilitates the spread of transboundary animal diseases such as Peste des petits ruminants (PPR). In Nigeria, PPR outbreaks recur regularly, yet surveillance and control remain limited in the absence of routine animal-movement tracking. Here, we assess and compare movement-informed control options for PPR using a reconstructed livestock mobility network from a one-time market survey conducted in three northern Nigerian states. We simulate transmission on this network and evaluate three intervention strategies: (i) targeting vulnerable villages, (ii) targeting the links that connect movement communities, and (iii) targeting villages belonging to the network backbone. Across scenarios, backbone-based targeting consistently produced the largest reductions in network connectivity and epidemic outcomes, outperforming strategies focused on vulnerable nodes or inter-community links. These results suggest that backbone-informed control could provide a practical, resource-efficient pathway to strengthen PPR control in settings where routine movement data are scarce.

In October 2019, South Korea’s first case of African swine fever (ASF) was reported in wild boar in the north of the country. Despite the implementation of a 2300 km-long fencing strategy, the ASF wavefront continued to invade southward. Our study aimed to investigate the ASF wavefront dynamics in different regions of South Korea, as well as to assess the effectiveness of the fencing measures on ASF dispersal and wavefront velocity. From the nationwide wild boar surveillance system, we extracted 2661 cases, starting from 2 October 2019 (first detection) to 15 September 2022. The cases were categorised into four main spatiotemporal clusters. The average wavefront velocity over the four clusters was estimated at 0.52 km/week, with the cluster in the eastern part of the Korean peninsula exhibiting the fastest velocity (0.99 km/week) compared to the other clusters (0.44, 0.31, and 0.15 km/week). We hypothesise that these differences are related to different wild boar densities due to heterogeneous habitat suitability. We also found that fencing significantly impacted ASF dispersal in only two of the four main clusters, with no evidence that fencing slowed down the spread of the wavefront in any of the clusters. We argue that this heterogeneity might result from fencing locations being misaligned with the true (and unobserved) wavefront.

Peste des petits ruminants (PPR) is a highly contagious disease affecting mainly sheep and goats. Livestock movements contribute to the spread of the disease by introducing it to naive areas or exposing susceptible animals to it in infected regions. Because of its socio-economic impact, the Food and Agriculture Organisation (FAO) and the World Organization for Animal Health (WOAH) have set the goal to eradicate it by 2030, one of the key steps being the improvement of surveillance networks. The present study aimed to provide tools to identify areas that could serve as sentinel nodes, i.e. areas that may be rapidly infected at the onset of epidemics. Using data from a market survey conducted in Northern Nigeria, we reconstructed the small ruminants mobility network and simulated the diffusion of PPR virus through animal movement. From the analysis of simulation outcomes, we investigated which nodes could act as sentinel nodes under specific conditions for disease transmission. We considered several modified networks to get around the problem of data only being available for part of the overall network structure and to account for potential errors made during the field study. For each configuration, we simulated the spread of PPR using a stochastic Susceptible-Infectious (SI) model based on animal movements to assess the epidemics' extent and the presence of recurrent patterns to identify potential sentinel nodes. We extracted the backbone of the reference network and checked for the presence of sentinel nodes within it. We investigated how the origin (seed) of the epidemics could affect the propagation pattern by comparing and grouping seeds based on their respective transmission paths. Results showed that the isolated backbone contains 45% of sentinel nodes that remain stable or undergo only minor changes in 9 out of 11 configurations. On top of that, the characteristics of sentinel nodes identified in the backbone are not influenced by the severity of the disease. The H index, in-degree, and eigenvector are the most essential variables. This study provides an overview of the major axes of animal movements in Nigeria and the most vulnerable locations that should be prioritized for monitoring livestock diseases like PPR.

Animal mobility is a founding element of pastoral culture and fundamental to the economy in West Africa. Herds movement, involving mainly cattle, sheep, and goats, is vital for adapting to climate fluctuations, optimizing natural resources, and managing risks in livestock production, as well as livestock trade and exchanges. However, these movements contribute to the spread of transboundary animal diseases such as Peste des petits ruminants (PPR). Nigeria experienced its first PPR outbreak in the 1960s-1970s, and outbreaks have regularly occurred since then. Yet, no adequate surveillance system has been put in place, and the absence of proper animal movement tracking remains a critical shortcoming in addressing this ongoing threat. Because of this, we rely on ad-hoc activities, like mobility surveys, to collect this information. However, these data could be partial and limited in time and space, hindering the capacity to identify suitable areas for monitoring disease circulation (sentinel nodes). Market survey data from three northern states are collected once to reconstruct the small ruminant mobility network. A group of areas with a high potential to infect each other were identified (Contagion Cluster). A stochastic Susceptible-Infected-Recovered (SIR) was used to simulate the spread of a PPR-like disease through movements. Sentinel nodes and their key characteristics were identified using Random Forest classification. The network (missing movement) was predicted with a hierarchical random graph (HRG), and uncertainty analysis assessed the effects of missing movements on the epidemic extent and identity and characteristics of sentinel nodes. The number of sentinel nodes varied with the epidemic severity, but their characteristics remained consistent. The uncertainty analysis results showed that adding 1% of the most probable missing links did not affect the final size of the epidemic. However, a significant difference appears when adding more than 3% of the missing links, causing a gradual fluctuation in the epidemic final size. The final size of the epidemic stabilized when adding more than 50% of the most probable links. The challenge posed by incomplete animal movement data underscores the need for further research and data collection efforts. However, predicting missing links presents a promising method for enhancing the reliability of epidemic prediction and sentinel node identification. This potential to improve disease surveillance and control strategies is a significant implication of our study. ### Competing Interest Statement The authors have declared no competing interest.

African swine fever (ASF) has devastating effects on swine production, farmer livelihood, animal welfare, and biodiversity. Extremely difficult to control, epidemic management is further complicated when spillover between domestic pig and wild boar populations is suspected. To quantify ASF viral transmission between domestic pigs and wild boar, a spatially-explicit stochastic mechanistic model was constructed using village centroids to represent aggregated backyard pig herds and a hexagonal raster of forest coverage to represent wild boar abundance. The model was parameterized to the initial six months of the ongoing Romanian epidemic through approximate Bayesian computation. It was estimated that a median of 69.4% (interquartile range: 53.0–80.0%) of domestic pig herd cases came from other infected domestic pig herds while 20.4% (11.2–33.8%) originated from infected wild boar sources, and 8.4% (4.7–14.2%) stemmed from external sources not explicitly represented. Also, 31.9% of infected wild boar habitat (16.7–56.2%) originated from domestic pig herds and 68.1% (43.8–83.3%) came from neighboring infected wild boar populations. Furthermore, it was found that habitats with a forest coverage greater than 15% were 2.6 times more infectious and 5.3 times more susceptible than other habitats. All alternative control scenarios, including culling domestic pig herds upon local domestic pig or wild boar case detection, improved epidemic outcomes, with the greatest decrease in final epidemic size being observed from the reactive culling of entire villages following case detection. These results can be used to further inform policy recommendations in ASF-epidemic regions.Significance Statement The current African swine fever (ASF) pandemic is devastating to affected nations, and quantifying transmission parameters is critical to informing control strategies. Disease spillover between wild and domestic hosts further complicates control efforts, yet the influence of spillover events on epidemic propagation remains unknown. Using the context of Romania—one of the European nations with the most severe epidemic and where spillover transmission is strongly suspected—we show that targeting spillover mechanisms is critical for achieving holistic disease control, and then demonstrate the impact of alternative control scenarios had they been enacted. These results can inform control strategy policy decisions in the many nations at-risk for or actively experiencing ASF epidemics.### Competing Interest StatementThe authors have declared no competing interest.

The control of epidemics requires a thorough understanding of the complex interactions between pathogen transmission, disease impact, and population dynamics and management. Mechanistic epidemiological modelling is an effective way to address this issue, but handling highly structured and dynamic systems, remains challenging. We therefore developed a novel approach that combines Multi-Level Agent-Based Systems (MLABS) with spatial and temporal organization, allowing for a tuned representation of the transmission processes amongst the host population. We applied this method to model the spread of a PRRSv-like virus in pig farms, integrating the clinical consequences (conception and reproduction failures), in terms of animal husbandry practices. Results highlighted the importance to account for spatial and temporal structuring and herd management policies in epidemiological models. Indeed, disease-related abortions, inducing reassignments of sows in different batches, was shown to enhance the transmission process, favouring the persistence of the virus at the herd level. Supported by a declarative Domain-Specific Language (DSL), our approach provides flexible and powerful solutions to address the issues of on-farm epidemics and broader public health concerns. The present application, based on a simple Susceptible-Exposed-Infected-Recovered (SEIR) model, opens the way to the representation of more complex epidemiological systems, including more specific features such as maternally derived antibodies, vaccination, or dual infections, along with their respective clinical consequences on the management practices.

Peste des Petits Ruminants (PPR) is a highly contagious disease affecting sheep and goats and spreading through livestock movements. The FAO and WOAH have set the goal to eradicate it by 2030, with one of the key steps being the improvement of surveillance networks. In our study, we utilize an SI model to simulate the spread of PPR across three Nigerian States due to animal movements. Our objective is to identify areas that could serve as potential sentinel nodes, which are nodes that may become infected promptly at the onset of epidemics. We reconstructed the mobility network using (the partial) movement data collected through market surveys. Due to the limitations of the study, we implement plausible network modifications and generated eight distinct network configurations. For each of these configurations, we assessed the extent of the epidemics, the presence of recurrent patterns and characterize sentinel nodes. Our findings indicate that minor network modifications do not impact the final sizes of epidemics. However, removing a central market or introducing a significant number of new links can lead to noticeable shifts in epidemic propagation trajectories. Regardless of the specific configurations considered, we identified three clusters of epidemic origins, each exhibiting distinct behaviors. Nevertheless, geographical proximity among these origins does not necessarily imply similar transmission patterns. Furthermore, our study highlights that, in most configurations, attributes such as the in-H index, eigenvector and in-degree centralities emerge as the most influential factors in defining vulnerable nodes. Therefore, we recommend prioritizing data collection efforts in central markets due to their wealth of information resources

Background Porcine reproductive and respiratory syndrome (PRRS) is a viral disease with worldwide distribution and an enormous economic impact. To control PRRS virus (PRRSV) infection, modified live vaccines (MLVs) are widely used in the field, mainly administered via an intramuscular (IM) route. Currently, some MLVs are authorized for intradermal (ID) administration, which has many practical and welfare advantages. The objectives of the study were to compare the immune responses (systemic in blood and mucosal in lungs) and vaccine efficacy in preventing challenge strain transmission after IM or needle-free ID immunization of piglets with an MLV against PRRSV-1 (MLV1). Methods Groups of sixteen 5-week-old specific pathogen-free piglets were vaccinated with Porcilis PRRS® (MSD) either by an IM (V+ IM) or ID route (V+ ID) using an IDAL®3G device or kept unvaccinated (V-). Four weeks after vaccination, in each group, 8 out of the 16 piglets were challenged intranasally with a PRRSV-1 field strain, and one day later, the inoculated pigs were mingled by direct contact with the remaining 8 sentinel noninoculated pigs to evaluate PRRSV transmission. Thus, after the challenge, each group (V+ IM, V+ ID or V-) included 8 inoculated and 8 contact piglets. During the postvaccination and postchallenge phases, PRRSV replication (RT–PCR), PRRSV-specific antibodies (ELISA IgG and IgA, virus neutralization tests) and cell-mediated immunity (ELISPOT Interferon gamma) were monitored in blood and bronchoalveolar lavages (BALs). Results Postvaccination, vaccine viremia was lower in V+ ID pigs than in V+ IM pigs, whereas the cell-mediated immune response was detected earlier in the V+ ID group at 2 weeks postvaccination. In the BAL fluid, a very low mucosal immune response (humoral and cellular) was detected. Postchallenge, the vaccine efficacy was similar in inoculated animals with partial control of PRRSV viremia in V+ ID and V+ IM animals. In vaccinated sentinel pigs, vaccination drastically reduced PRRSV transmission with similar estimated transmission rates and latency durations for the V+ IM and V+ ID groups. Conclusions Our results show that the tested MLV1 induced a faster cell-mediated immune response after ID immunization two weeks after vaccination but was equally efficacious after IM or ID immunization towards a challenge four weeks later. Considering the practical and welfare benefits of ID vaccination, these data further support the use of this route for PRRS MLVs.

Peste des Petits Ruminants (PPR) is a highly contagious disease that mainly affects sheep and goats and is transmitted through livestock movements. Because of its socio-economic impact, the Food and Agriculture Organisation (FAO) and the World Organization for Animal Health (WOAH) have set the goal to eradicate it by 2030, one of the key steps being the improvement of surveillance networks. The present study aimed to provide tools to identify areas that could serve as sentinel nodes , i.e. areas that may be rapidly infected at the onset of epidemics. Using data from a market survey conducted in the Northern Region of Nigeria, we analyzed which nodes, under which conditions, could serve as sentinel nodes. We considered several modified networks to get around the problem of data only being available for part of the overall network structure and to account for potential errors made during the field study. For each configuration, we simulated the spread of PPR using a stochastic Susceptible-Infectious (SI) model based on animal movements to assess the epidemics’ extent and the presence of recurrent patterns to identify potential sentinel nodes . We extracted the backbone of the reference network and checked for the presence of sentinel nodes within it. We then explored the possibility of using the backbone nodes as sentinel nodes. We investigated how the origin (seed) of the epidemics could affect the propagation pattern by comparing and grouping seeds based on their respective transmission paths. Results showed that the isolated backbone contains 45% sentinel nodes that remain stable or undergo only minor changes in 9 out of 11 configurations. On top of that, the characteristics of sentinel nodes identified in the backbone are not influenced by the severity of the disease. The H index, in-degree, and eigenvector are the most essential variables. This study provides an overview of the major axes of animal movements in Nigeria and the most vulnerable locations that should be prioritized for monitoring livestock diseases like PPR. ### Competing Interest Statement The authors have declared no competing interest.

Swine influenza A virus (swIAV) is a major pathogen affecting pigs with a huge economic impact and potentially zoonotic. Epidemiological studies in endemically infected farms permitted to identify critical factors favoring on-farm persistence, among which maternally-derived antibodies (MDAs). Vaccination is commonly practiced in breeding herds and might be used for immunization of growing pigs at weaning. Althoughinterference between MDAs and vaccination was reported in young piglets, its impact on swIAV transmission was not yet quantified. To this aim, this study reports on a transmission experiment in pig-lets with or without MDAs, vaccinated with a single dose injection at four weeks of age, and challenged 17 days post-vaccination. To transpose small-scale experiments to real-life situation, estimated parame-ters were used in a simulation tool to assess their influence at the herd level.Based on a thorough follow-up of the infection chain during the experiment, the transmission of the swIAV challenge strain was highly dependent on the MDA status of the pigs when vaccinated. MDA-positive vaccinated animals showed a direct transmission rate 3.6-fold higher than the one obtained in vaccinated animals without MDAs, estimated to 1.2. Vaccination nevertheless reduced signif-icantly the contribution of airborne transmission when compared with previous estimates obtained in unvaccinated animals.The integration of parameter estimates in a large-scale simulation model, representing a typical farrow-to-finish pig herd, evidenced an extended persistence of viral spread when vaccination of sows and single dose vaccination of piglets was hypothesized. When extinction was quasi-systematic at year 5 post-introduction in the absence of sow vaccination but with single dose early vaccination of piglets, the extinction probability fell down to 33% when batch-to-batch vaccination was implemented both in breeding herd and weaned piglets.These results shed light on a potential adverse effect of single dose vaccination in MDA-positive piglets, which might lead to longer persistence of the SwIAV at the herd level.(c) 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

SARS-CoV-2 in infected patient mainly display pulmonary and oronasal tropism however, the presence of the virus has also been demonstrated in stools of patients and consequently in wastewater treatment plant effluents, questioning the potential risk of environmental contamination (such as seawater contamination) through inadequately treated wastewater spill-over into surface or coastal waters. The environmental detection of RNA alone does not substantiate risk of infection, and evidence of an effective transmission is not clear where empirical observations are lacking.Therefore, here, we decided to experimentally evaluate the persistence and infectious capacity of the Porcine epidemic diarrhea virus (PEDv), considered as a coronavirus representative model and SARS-CoV-2 surrogate, in the coastal environment of France. Coastal seawater was collected, sterile-filtered, and inoculated with PEDv before incubation for 0–4 weeks at four temperatures representative of those measured along the French coasts throughout the year (4, 8, 15, and 24°C). The decay rate of PEDv was determined using mathematical modeling and was used to determine the half-life of the virus along the French coast in accordance with temperatures from 2000 to 2021.We experimentally observed an inverse correlation between seawater temperature and the persistence of infectious viruses in seawater and confirm that the risk of transmission of infectious viruses from contaminated stool in wastewater to seawater during recreational practices is very limited. The present work represents a good model to assess the risk of transmission of not only SARS-CoV-2 but may also be used to model the risk of other coronaviruses, specifically enteric coronaviruses.Importance This present work is a follow up addressing the question of the persistence of coronavirus in marine environment owing to the fact that SARS-CoV-2 is regularly detected in wastewater treating plan and the coastal environment is particularly at risk since it is subjected to increasing anthropogenic pressure and is the final receiver of surface waters and treated or sometimes insufficiently depurated waste waters. Our findings are of interest to researchers and authorities seeking to monitor SARS-CoV-2 and also enteric coronaviruses in the environment, either in tourist areas or in regions of the world, where centralized systems for wastewater treatment are not implemented, and more broadly, to the scientific community involved in “One Health” approaches.### Competing Interest StatementThe authors have declared no competing interest.### Funding StatementThis work is supported by the Agence Nationale de la Recherche and the Fondation de France (ANR RA-Covid wave 5, 00109676), the Region Pays de la Loire (order 2020-12887), by an internal funding from Ifremer General Direction (SARS-CoV-2 action plan) and the European project VEO (H2020, SC1-2019-874735).### Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesI confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.YesAll data produced in the present study are available upon reasonable request to the authors

The present work addresses the question of the persistence of coronavirus in marine environments because SARS-CoV-2 is regularly detected in wastewater treatment plants, and the coastal environment, subjected to increasing anthropogenic pressure and the final receiver of surface waters and sometimes insufficiently depurated wastewater, is particularly at risk. The problem also arises in the possibility of soil contamination by CoV from animals, especially livestock, during manure application, where, by soil impregnation and runoff, these viruses can end up in seawater.

Modeling of infectious diseases at the livestock-wildlife interface is a unique subset of mathematical modeling with many innate challenges. To ascertain the characteristics of the models used in these scenarios, a scoping review of the scientific literature was conducted. Fifty-six studies qualified for inclusion. Only 14 diseases at this interface have benefited from the utility of mathematical modeling, despite a far greater number of shared diseases. The most represented species combinations were cattle and badgers (for bovine tuberculosis, 14), and pigs and wild boar [for African (8) and classical (3) swine fever, and foot-and-mouth and disease (1)]. Assessing control strategies was the overwhelming primary research objective (27), with most studies examining control strategies applied to wildlife hosts and the effect on domestic hosts (10) or both wild and domestic hosts (5). In spatially-explicit models, while livestock species can often be represented through explicit and identifiable location data (such as farm, herd, or pasture locations), wildlife locations are often inferred using habitat suitability as a proxy. Though there are innate assumptions that may not be fully accurate when using habitat suitability to represent wildlife presence, especially for wildlife the parsimony principle plays a large role in modeling diseases at this interface, where parameters are difficult to document or require a high level of data for inference. Explaining observed transmission dynamics was another common model objective, though the relative contribution of involved species to epizootic propagation was only ascertained in a few models. More direct evidence of disease spill-over, as can be obtained through genomic approaches based on pathogen sequences, could be a useful complement to further inform such modeling. As computational and programmatic capabilities advance, the resolution of the models and data used in these models will likely be able to increase as well, with a potential goal being the linking of modern complex ecological models with the depth of dynamics responsible for pathogen transmission. Controlling diseases at this interface is a critical step toward improving both livestock and wildlife health, and mechanistic models are becoming increasingly used to explore the strategies needed to confront these diseases.