Browsing by Author "Ssematimba, A."

Now showing 1 - 3 of 3
  • Thumbnail Image
    Item
    Estimating the between-farm transmission rates for highly pathogenic avian influenza subtype H5N1 epidemics in Bangladesh between 2007 and 2013
    (Transboundary and emerging diseases, 2018) Ssematimba, A.; Okike, I.; Ahmed, G. M.; Yamage, M.; Boender, G. J.; Hagenaars, T. J.; Bett, B.
    Highly Pathogenic Avian Influenza (HPAI) is classified by the World Organization for Animal Health as one of the notifiable diseases. Its occurrence is associated with severe socio-economic impacts and is also zoonotic. Bangladesh HPAI epidemic data for the period between 2007 and 2013 were obtained and split into epidemic waves based on the time lag between outbreaks. By assuming the number of newly infected farms to be binomially distributed, we fit a Generalized Linear Model to the data to estimate between-farm transmission rates (b). These parameters are then used together with the calculated infectious periods to estimate the respective basic reproduction numbers (R0). The change in b and R0 with time during the course of each epidemic wave was explored. Finally, sensitivity analyses of the effects of reducing the delay in detecting infection on a farm as well as extended infectiousness of a farm beyond the day of culling were assessed. The point estimates obtained for b ranged from 0.08 (95% CI: 0.06–0.10) to 0.11 (95% CI: 0.08–0.20) per infectious farm per day while R0 ranged from 0.85 (95% CI: 0.77–1.02) to 0.96 (95% CI: 0.72–1.20). Sensitivity analyses reveal that the estimates are quite robust to changes in the assumptions about the day in reporting infection and extended infectiousness. In the analysis allowing for time-varying transmission parameters, the rising and declining phases observed in the epidemic data were synchronized with the moments when R0 was greater and less than one, respectively. From an epidemiological perspective, the consistency of these estimates and their magnitude (R0 1) indicate that the effectiveness of the deployed control measures was largely invariant between epidemic waves and the trend of the time-varying R0 supports the hypothesis of sustained farm-tofarm transmission that is possibly initiated by a few unique introductions.
  • Thumbnail Image
    Item
    Estimating within-flock transmission rate parameter for H5N2 highly pathogenic avian influenza virus in Minnesota turkey flocks during the 2015 epizootic
    (Epidemiology and Infection, 2019) Ssematimba, A.; Malladi, S.; Hagenaars, T. J.; Bonney, P. J.; Weaver, J. T.; Patyk, K. A.; Spackman, E.; Halvorson, D. A.; Cardona, C. J.
    Better control of highly pathogenic avian influenza (HPAI) outbreaks requires deeper understanding of within-flock virus transmission dynamics. For such fatal diseases, daily mortality provides a proxy for disease incidence. We used the daily mortality data collected during the 2015 H5N2 HPAI outbreak in Minnesota turkey flocks to estimate the within-flock transmission rate parameter (β). The number of birds in Susceptible, Exposed, Infectious and Recovered compartments was inferred from the data and used in a generalised linear mixed model (GLMM) to estimate the parameters. Novel here was the correction of these data for normal mortality before use in the fitting process. We also used mortality threshold to determine HPAI-like mortality to improve the accuracy of estimates from the back-calculation approach. The estimated β was 3.2 (95% confidence interval (CI) 2.3–4.3) per day with a basic reproduction number of 12.8 (95% CI 9.2–17.2). Although flock-level estimates varied, the overall estimate was comparable to those from other studies. Sensitivity analyses demonstrated that the estimated β was highly sensitive to the bird-level latent period, emphasizing the need for its precise estimation. In all, for fatal poultry diseases, the back-calculation approach provides a computationally efficient means to obtain reasonable transmission parameter estimates from mortality data.
  • Thumbnail Image
    Item
    Mathematical model for COVID-19 management in crowded settlements and high-activity areas
    (International Journal of Dynamics and Control, 2021) Ssematimba, A.; Nakakawa, J. N.; Ssebuliba, J.; Mugisha, J. Y. T.
    This paper develops and analyses a habitat area size dependent mathematical model to study the transmission dynamics of COVID-19 in crowded settlements such as refugee camps, schools, markets and churches. The model quantifies the potential impact of physical/social distancing and population density on the disease burden. Results reveal that with no fatalities and no infected entrants, the reproduction numbers associated with asymptomatic and symptomatic cases are inversely proportional to; the habitat area size, and the efforts employed in tracing and hospitalising these cases. The critical habitat area below which the disease dies out is directly proportion to the time taken to identify and hospitalise infected individuals. Results also show that disease persistence in the community is guaranteed even with minimal admission of infected individuals. Our results further show that as the level of compliance to standard operating procedures (SOPs) increases, then the disease prevalence peaks are greatly reduced and delayed. Therefore, proper adherence to SOPs such as use of masks, physical distancing measures and effective contact tracing should be highly enforced in crowded settings if COVID-19 is to be mitigated.