Moslem Soodejani; Ali Akbar Haghdoost; Mohammad Reza Baneshi; Abbas Sedaghat; Seyyed Mohammad Tabatabaei; Farzaneh Zolala
Abstract
Background: The prevalence of infections among general population can affect the prevalence among blood donors. Due to to the importance of blood safety, this study was conducted to estimate the prevalence of HIV, HBV, and HCV in donated bloods in Iran in 2018.Methods: Using information of 1,308,284 ...
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Background: The prevalence of infections among general population can affect the prevalence among blood donors. Due to to the importance of blood safety, this study was conducted to estimate the prevalence of HIV, HBV, and HCV in donated bloods in Iran in 2018.Methods: Using information of 1,308,284 blood donors, we designed this cross-sectional study to estimate the prevalence of transfusion-transmitted infections (TTIs) in Iranian blood donors. All the prevalence was reported per 100,000 population.Results: HIV prevalence in blood donors was about 2 per 100,000 (95% CI: 1.999, 2.001) population. Prevalence of HBV and HCV was 53(95% CI: 52.999-53.00) and 26 (95% CI: 25.999-26.001), respectively.Conclusion: It seems that the screening of volunteers would defer many people who may have been infected with TTIs; as a result, people with the least risk of being infected are selected to donate blood. Notice: All of these infected bloods were detected and discarded from the blood donation chain.
Vahid Rahmanian; Saied Bokaie; Aliakbar Haghdoost; Mohsen Barouni
Abstract
Background: Visceral leishmaniasis (VL) is a neglected infection currently occurring in some regions of Europe, Asia, Africa, and America. This study was an attempt to determine the temporal patterns of VL from January 2000 to December 2019 in the Ardabil Province of north-western Iran using the Markov ...
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Background: Visceral leishmaniasis (VL) is a neglected infection currently occurring in some regions of Europe, Asia, Africa, and America. This study was an attempt to determine the temporal patterns of VL from January 2000 to December 2019 in the Ardabil Province of north-western Iran using the Markov Switching Models (MSM).Methods: This descriptive study used monthly data of 602 VL cases during the study period. The data were provided by the Leishmaniasis National Surveillance System (LNSS), the Iran Meteorological Organization (IMO), and Space Agency (SA), and two states were considered for such modelling. Given the Akaike and Bayesian information criterion, the two-state MSM with a five-month lag is an appropriate model.Results: The MSM showed that the probability of staying in the non-epidemic state is 67%, (P11), while that of staying in an epidemic state is 93% (P22). The mean absolute percentage error (MAPE) was 31.63%, and the portmanteau test (Q=19.03, P=0.66) for the residuals of the selected model revealed that the data were completely modelled. The total VL cases in the next 24 months forecasted 14 cases.Conclusion: The MSM has a relatively acceptable predictive power and is useful in planning future interventions with more information about different stages of the epidemic it provides to policymakers for early warning of epidemics.
