arXiv subjects

Nicolas C. Cardenas

Publications and source records attributed to Nicolas C. Cardenas.

6 recordsLinked to original sources

arXiv2026

Multi-network comparison of between-farm contacts for infectious disease surveillance in swine production

Understanding how swine farms are interconnected, directly and indirectly, is essential to characterizing infectious disease transmission. This study aimed to describe the connectivity of swine farms across 11 network types, including vehicle movements (i.e., trucks and trailers), animal movements, and distance-based farm-to-farm contacts, to identify links among production types and farms likely to be consistently characterized as super-spreaders. Truck and trailer movement networks were the most densely connected, particularly for feed transport, showing connectivity levels between 98.7% and 99.7% higher than those of pig movement and distance-based networks. These networks also exhibited the highest degree and frequency of connections between farms, while the aggregated truck network, which included all truck types, showed the greatest potential to act as a bridge connecting farms. Finisher farms were highly interconnected with other farm types across all networks. Sow farms were frequently reached by other farm types, especially through feed truck movements, representing up to 8.7% of these links. We demonstrated that in vehicle movements and proximity networks, finisher farms played a major role as super-spreaders. When comparing the top 50 farms ranked by super-spreader score in each network, vehicle-based networks showed the highest similarity, with up to 89% of top-ranked farms shared between vehicle networks. In contrast, pig movement and distance-based networks identified largely distinct sets of top-ranked farms, sharing at most 4% and 8%, respectively, with other contact networks. Overall, each network exhibited a distinct connectivity structure, resulting in different sets of high-risk farms, particularly regarding potential transmission to breeding farms. These findings support the integration of multiple transmission pathways into disease surveillance.

physics.soc-ph↗

arXiv2026

A Modelling Assessment of the Impact of Control Measures on Simulated Foot-and-Mouth Disease Spread in Mato Grosso do Sul, Brazil

This study simulated the introduction of Foot-and-mouth disease (FMD) into Mato Grosso do Sul, Brazil, to evaluate the effectiveness of outbreak control strategies. Our susceptible-exposed-infected-recovered model generated a range of outbreak sizes across the state. These outbreaks were used to model control actions across six scenarios: high vaccination, two variations of moderate depopulation combined with vaccination, high depopulation with limited vaccination, and moderate and high depopulation alone. Our results showed that relying solely on high vaccination was the least effective approach; it controlled only 2.22 % of outbreaks and resulted in the highest number of infected farms and the longest control duration. Mixed strategies, busing, moderate depopulation, and vaccination controlled approximately 91 % of outbreaks. The use of moderate depopulation alone controlled 96.60 % of outbreaks, and it was 14-15 days faster than the mixed approaches. The most effective strategy combined the highest depopulation capacity with limited vaccination, controlling 100 % of outbreaks and producing the shortest control duration. The number of vaccinated animals ranged from 211,002 under the optimal strategy to 596,530 when the control strategy included only vaccination. We demonstrated that vaccination alone was insufficient to eliminate outbreaks, and that depopulation and vaccination strategies would be required to stamp out future FMD introduction in Mato Grosso do Sul (MS). The success of such a strategy would eliminate between 90 % to 100 % of outbreaks in 10 to 15 days and reduce the number of infected farms by 10 to 13.

q-bio.PE↗

arXiv2025

First highly pathogenic avian influenza outbreak in a commercial farm in Brazil: outbreak timeline, control actions, risk analysis, and transmission modeling

On May 15, 2025, Brazil reported its first highly pathogenic avian influenza (HPAI) outbreak in a commercial poultry breeder farm in Montenegro, Rio Grande do Sul. This study presents the outbreak timeline, control measures, along with spatial risk assessment and epidemiological model used to simulate detection delays. The transmission model considered Susceptible Exposed Infected Recovered Dead farm statuses to simulate within farm and between farm dynamics under 3 day, 5 day, and 10 day detection delays. The single infected commercial farm lost 15,650 birds, with 92% mortality due to HPAI, and additional culling of the remaining birds on Day 5 post-notification to the state animal health officials. Based on the mortality and outbreak response data, the introduction likely occurred 3 10 days before its official detection. Our field investigations suggested that wild birds were the most likely source of introduction, although biosecurity breaches could not be ruled out. Control measures implemented included movement restrictions and a control zone, from which 4,197 vehicles were inspected upon entry. Risk analysis classified 64.4% of municipalities as low risk, 35.0% as medium risk, and 0.6% as high risk. Our HPAI disease simulation results showed that the number of secondary infections would increase from a median of 4 farms (IQR 2 5) with a 3 day delay to 6 (IQR 3 22) and 34 (IQR 12 47) farms with 5 day and 10 day delays, respectively. The rapid veterinary response eliminated the outbreak within 32 days of detection, highlighting the critical role of early detection and prompt response.

q-bio.PE↗

arXiv2025

Simulating foot-and-mouth dynamics and control in Bolivia

Examining the dissemination dynamics of foot-and-mouth disease (FMD) is critical for revising national response plans. We developed a stochastic SEIR metapopulation model to simulate FMD outbreaks in Bolivia and explore how the national response plan impacts the dissemination among all susceptible species. We explored variations in the control strategies, mapped high-risk areas, and estimated the number of vaccinated animals during the reactive ring vaccination. Initial outbreaks ranged from 1 to 357 infected farms, with control measures implemented for up to 100 days, including control zones, a 30-day movement ban, depopulation, and ring vaccination. Combining vaccination (50-90 farms/day) and depopulation (1-2 farms/day) controlled 60.3% of outbreaks, while similar vaccination but higher depopulation rates (3-5 farms/day) controlled 62.9% and eliminated outbreaks nine days faster. Utilizing depopulation alone controlled 56.76% of outbreaks, but had a significantly longer median duration of 63 days. Combining vaccination (25-45 farms/day) and depopulation (6-7 farms/day) was the most effective, eliminating all outbreaks within a median of three days (maximum 79 days). Vaccination alone controlled only 0.6% of outbreaks and had a median duration of 98 days. Ultimately, results showed that the most effective strategy involved ring vaccination combined with depopulation, requiring a median of 925,338 animals to be vaccinated. Outbreaks were most frequent in high-density farming areas such as Potosi, Cochabamba, and La Paz. Our results suggest that emergency ring vaccination alone can not eliminate FMD if reintroduced in Bolivia, and combining depopulation with vaccination significantly shortens outbreak duration. These findings provide valuable insights to inform Bolivia national FMD response plan, including vaccine requirements and the role of depopulation in controlling outbreaks.

q-bio.PE↗

arXiv2025

Integrating epidemiological and economic models to estimate the cost of simulated foot-and-mouth disease outbreaks in Brazil

The introduction of foot-and-mouth disease (FMD) leads to substantial economic impacts through animal loss, decreased livestock and meat production, increased government and private spending on control and eradication measures, and trade restrictions. This study evaluates the direct cost-effectiveness of four control and eradication scenarios of hypothetical FMD outbreaks in Rio Grande do Sul, Brazil. Our model simulation considered scenarios with depopulation of detected farms and emergency vaccination and two enhanced scenarios featuring increased capacity for emergency vaccination and depopulation. FMD outbreaks were simulated using a multi-host, single-pathogen Susceptible-Exposed-Infectious-Recovered model incorporating species-specific transmission probabilities, within-farm dynamics, and spatial transmission factors. The economic cost evaluation encompassed animal elimination (a.k.a. depopulation), carcass disposal, visits by animal health officials, laboratory testing, emergency vaccination, and sanitary barriers (a.k.a. traffic-control points), and movement restrictions due to control zones. Our results provided a range of predicted costs for a potential reintroduction of FMD ranging from $977,128 to $52,275,811. Depopulation was the most expensive, followed by local traffic control points and emergency vaccination. Our results demonstrated that higher rates of depopulation, or depopulation combined with vaccination, were the most effective strategies to reduce long-term economic impacts despite higher initial costs. Allocating more resources early in the outbreak was cost-effective in minimizing the overall effect and achieving faster eradication.

q-bio.PE↗

arXiv2022

Multiple species animal movements: network properties, disease dynamic and the impact of targeted control actions

Infectious diseases in livestock are well-known to infect multiple hosts and persist through the combination of within- and between-host transmission pathways. Uncertainty remains about the epidemic consequences of the disease being introduced on farms with more than one susceptible host. Here we describe multi-host contact networks to elucidate the potential of disease spread among farms with multiple species. Four years of between-farm animal movement data of bovine, swine, small ruminants, and multi-host, were described through both static and time-series networks; the in-going and out-going contact chains were also calculated. We use the proposed stochastic multilevel model to simulate scenarios in which infection was seeded into a single host and multi-hosts farms, to estimate epidemic trajectories and simulate network-based control actions to assess the reduction of secondarily infected farms. Our analysis showed that the swine network was more connected than cattle and small ruminants in the temporal network view. The small ruminants network was shown disconnected, however, allowing the interaction among networks with different hosts enabling the spread of disease throughout the network. Independently from the initial infected host, secondary infections were observed crossing overall species. We showed that targeting the top 3.25% of the farms ranked by degree could reduce the total number of infected farms below 70% at the end of the simulation period. In conclusion, we demonstrated the potential of the multi-host network in disease propagation, therefore, it becomes important to consider the observed multi-host movement dynamics while designing surveillance and preparedness control strategies.

q-bio.QM↗