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We propose a new stochastic framework for analysing the dynamics of the immunity response of wildlife hosts against a disease-causing agent. Our study is motivated by the need to analyse the monitoring time-series data covering the period from 1975 to 1995 on bacteriological and serological tests-samples from great gerbils being the main host of Yersinia pestis in Kazakhstan. Based on a four-state continuous-time Markov chain, we derive a generalized nonlinear mixed-effect model for analysing the serological test data. The immune response of a host involves the production of antibodies in response to an antigen. Our analysis shows that great gerbils recovered from a plague infection are more likely to keep their antibodies to plague and survive throughout the summer-to-winter season than throughout the winter-to-summer season. Provided the seasonal mortality rates are similar (which seems to be the case based on a mortality analysis with abundance data), our finding indicates that the immune function of the sampled great gerbils is seasonal.

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and polyomavirus KI was most prevalent in adults 25-64 that died, which is the group most affected by HIV. No fatal cases due to the coronaviruses were detected in single infections in any age group. Influenza A and RSV was most detected in fatal cases in the elderly.Conclusion: Influenza, RSV, hMPV and rhinovirus infection is associated with severe respiratory disease in South Africa if compared to healthy controls. In fatal disease, rhinovirus and RSV may be true pathogens in children however in HIV positive adults the role of viruses such as KI polyomaviruses and Adenovirus needs further investigation.

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