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1.
Prev Vet Med ; 169: 104703, 2019 Aug 01.
Article in English | MEDLINE | ID: mdl-31311629

ABSTRACT

Pig production in Kenya is hampered by seasonal markets. As an alternative outlet for the finished pigs, several value-added meat-processing firms have been established. Sausage, which is produced using casings derived from intestines of pigs, is one form of processed meats. Kenya imports several kgs of natural casings every year; and a recent concern is Swine vesicular disease virus (SVDV), which has never been reported in Kenya, might be introduced via natural casings imported from Italy. To determine conditions (with associated probabilities) that could lead to the introduction of SVDV, a quantitative risk assessment model was developed. Using Monte Carlo simulations at 10,000 iterations, the probability of introducing SVDV was estimated to be 1.9x10-8. Based on the suggested volume of import and mitigations used in the analysis, contaminated casings derived from an estimated 0.003 (Range = 8.1x10-8 - 0.08) infected pigs will be included in the consignment each year. The critical pathway analysis revealed that rigorous surveillance programs in Italy have a potential to dramatically reduce the risk of introducing SVDV into Kenya by this route.


Subject(s)
Food Microbiology/methods , Meat Products/virology , Swine Vesicular Disease/epidemiology , Swine Vesicular Disease/prevention & control , Abattoirs , Animals , Enterovirus B, Human , Italy/epidemiology , Kenya/epidemiology , Monte Carlo Method , Risk Assessment , Swine
2.
J Health Care Poor Underserved ; 22(4 Suppl): 39-60, 2011.
Article in English | MEDLINE | ID: mdl-22102305

ABSTRACT

A novel influenza, Influenza A 2009 H1N1 virus outbreak, emerged in mid-April 2009, and by December 2009, spread across the world. This epidemiologic analysis uses the epidemiologic problem oriented approach to gather information for, and develop a quantitative risk assessment model that evaluates the likelihood of an influenza outbreak in the U.S., utilizing weekly incidence rates (WIR) and case fatality rates (CFR) stratified by age and the 10 U.S. regions. In addition ArcGIS was used to show variability regarding morbidity rate and WIR. Using data from the Centers for Disease Control and Prevention (CDC) Emerging Infections Program and applying Monte Carlo simulations with @Risk software, the analysis revealed morbidity to be highest in region 8 (1.27×10-2) and lowest in region 2 (0.13×10-2). Heat map results revealed WIR were higher in younger children, for all regions. Case fatality rates were 10 times greater in younger people than in older people and children. Using these different temporal-spatial epidemiologic methods can help decision-makers identify high-risk population clusters and help in prevention and control of pandemics.


Subject(s)
Influenza A Virus, H1N1 Subtype/isolation & purification , Influenza, Human/epidemiology , Influenza, Human/virology , Pandemics , Adolescent , Adult , Age Distribution , Age Factors , Aged , Centers for Disease Control and Prevention, U.S. , Child , Child, Preschool , Geographic Information Systems , Hospitalization/statistics & numerical data , Humans , Incidence , Influenza, Human/diagnosis , Middle Aged , Monte Carlo Method , Morbidity , Mortality , Risk , United States/epidemiology , Young Adult
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