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Probabilistic modeling for an integrated temporary acquired immunity with norovirus epidemiological data

Infectious Disease Modelling 2019年第1期4卷 99-114页

作者： Emmanuel de-Graft Johnson Owusu-Ansah benedict barnes Robert Abaidoo Hald Tine Anders Dalsgaard Anders Permin Torben Wilde Schou Department of Mathematics Faculty of Physical and Computational ScienceCollege of ScienceKwame Nkrumah University of Science and TechnologyKumasiGhana Laboratory of Integrated Statistical Applications(LISA) Faculty of Physical and Computational SciencesCollege of ScienceKwame Nkrumah University of Science and TechnologyKumasiGhana Regional Water and Environmental Sanitation Center-Kumasi College of EngineeringKwame Nkrumah University of Science and TechnologyKumasiGhana Department of Theoretical and Applied Biology Faculty of Bio ScienceCollege of ScienceKwame Nkrumah University of Science and TechnologyKumasiGhana Research Group of Genomic Epidemiology National Food InstituteTechnical University of DenmarkKgs LyngbyDenmark Food Safety and Zoonoses Department of Veterinary and Animal SciencesFaculty of Health and Medical SciencesUniversity of CopenhagenStigb€ojlen 41870 Frederiksberg CDenmark Office for Innovation and Sector Services AdministrationTechnical University of DenmarkAnker Engelunds Vej2800 Kgs LyngbyDenmark Environment and Toxicology DHIHorsholmDenmark

Integration of acquired immunity into microbial risk assessment for illness incidence is of no doubt essential for the study of susceptibility to *** this study,a probabilistic model was set up as dose response for infection and a mathematical derivation was carried out by integrating immunity to obtain probability of illness *** acquire immunity from epidemiology studies which includes six different Norovirus transmission scenarios such as symptomatic individuals infectious,pre-and post-symptomatic infectiousness(low and high),innate genetic resistance,genogroup 2 type 4 and those with no immune boosting by asymptomatic infection were *** results on illness inflation factor as a function of dose and exposure indicated that high frequency exposures had immense immunity build up even at high dose levels;hence minimized the probability of *** Norovirus transmission dynamics data,results showed,and immunity included models had a reduction of 2e6 logs of magnitude difference in disease burden for both population and individual probable illness ***,the magnitude order of illness for each dose response remained largely the same for all transmission scenarios;symptomatic infectiousness and no immune boosting after asymptomatic infectiousness also remained the same *** integration of epidemiological data on acquired immunity into the risk assessment,more realistic results were achieved signifying an overestimation of probable risk of illness when epidemiological immunity data are not *** finding supported the call for rigorous integration of temporary acquired immunity in dose-response in all microbial risk assessments.

关键词： Quantitative risk assessment Probabilistic modeling Immunity integrated modeling

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