Kontowicz, E. | bioRxiv Science

bioRxiv2022

A stochastic compartmental model to simulate intra- and inter-species influenza transmission in an indoor swine farm

Common in swine production worldwide, influenza causes significant reductions in feed efficiency and potential transmission to the workforce. Swine vaccines are not universally used in swine production, partly due to their limited efficacy because of continuously evolving influenza viruses. We evaluated the effects of vaccination, quarantine of infected pigs, and changes to workforce routine (ensuring workers moved from younger pig batches to older pig batches). A Susceptible-Exposed-Infected-Recovered model was used to simulate stochastic influenza transmission during a single production cycle on an indoor hog growing unit containing 4000 pigs and two workers. The absence of control practices resulted in 3,958 pigs [1 - 3972] being infected and a 0.61 probability of workforce infection. Quarantine of infected pigs the same day they became infectious was the single effective control practice, reducing the number of infected pigs to 3 [1 - 3961] and the probability of workforce infection to 0.27. The second-best control practice was mass pig vaccination (80% effective vaccine), which reduced the number of infected pigs to 23.5 [1 - 635] and the probability of workforce infection to 0.07. The third-best control practice was changing the worker routine by starting with younger to older pig batches, which reduced the number of infected pigs to 997 [1 - 1984] and the probability of workforce infection (0.22). All other control practices, when considered alone, showed little improvement in reducing total infected pigs and the probability of workforce infection. Combining all control strategies reduced the total number of infected pigs to 1 or 2 with a minimal probability of workforce infection (0.03 - 0.01). These findings suggest that non-pharmaceutical interventions can reduce the impact of influenza on swine production and reduce the risk of interspecies transmission when efficacious vaccines are unavailable. Therefore, these results can help prevent the emergence of influenza strains with pandemic potential.

microbiology↗

bioRxiv2021

Inclusion of environmentally themed search terms improved Elastic Net regression nowcasts of regional Lyme disease rates

Lyme disease is the most widely reported vector-borne disease in the United States. 95% of human cases are reported in the Northeast and upper Midwest. Human cases typically occur in the spring and summer months when an infected nymph Ixodid tick takes a blood meal. Current federal surveillance strategies report data on an annual basis, leading to nearly a year lag in national data reporting. These lags in reporting make it difficult for public health agencies to assess and plan for the current burden of Lyme disease. Implementation of a nowcasting model, using historical data to predict current trends, provides a means for public health agencies to evaluate current Lyme disease burden and make timely priority-based budgeting decisions. The objective of this study was to develop and compare the performance of nowcasting models using free data from Google Trends and Centers of Disease Control and Prevention surveillance reports for Lyme Disease. We developed two sets of elastic net models for five regions of the United States first using monthly proportional hit data from 21 disease symptoms and tick related terms and second using monthly proportional hit data from all terms identified via Google correlate plus 21 disease symptom and vector terms. Elastic net models using the larger term list were highly accurate (Root Mean Square Error: 0.74, Mean Absolute Error: 0.52, R2: 0.97) for four of the five regions of the United States. Including these more environmental terms improved accuracy 1.33-fold while reducing error 0.5-fold compared to predictions from models using disease symptom and vector terms alone. Models using Google data similar to this could help local and state public health agencies accurately monitor Lyme disease burden during times of reporting lag from federal public health reporting agencies.

systems biology↗