Publication: Predicting factors for malaria re-introduction: An applied model in an elimination setting to prevent malaria outbreaks
Issued Date
2016-03-02
Resource Type
ISSN
14752875
Other identifier(s)
2-s2.0-84959453923
Rights
Mahidol University
Rights Holder(s)
SCOPUS
Bibliographic Citation
Malaria Journal. Vol.15, No.1 (2016)
Suggested Citation
Mansour Ranjbar, Alireza Shoghli, Goodarz Kolifarhood, Seyed Mehdi Tabatabaei, Morteza Amlashi, Mahdi Mohammadi Predicting factors for malaria re-introduction: An applied model in an elimination setting to prevent malaria outbreaks. Malaria Journal. Vol.15, No.1 (2016). doi:10.1186/s12936-016-1192-y Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/40828
Research Projects
Organizational Units
Authors
Journal Issue
Thesis
Title
Predicting factors for malaria re-introduction: An applied model in an elimination setting to prevent malaria outbreaks
Abstract
© 2016 Ranjbar et al. Background: Malaria re-introduction is a challenge in elimination settings. To prevent re-introduction, receptivity, vulnerability, and health system capacity of foci should be monitored using appropriate tools. This study aimed to design an applicable model to monitor predicting factors of re-introduction of malaria in highly prone areas. Methods: This exploratory, descriptive study was conducted in a pre-elimination setting with a high-risk of malaria transmission re-introduction. By using nominal group technique and literature review, a list of predicting indicators for malaria re-introduction and outbreak was defined. Accordingly, a checklist was developed and completed in the field for foci affected by re-introduction and for cleared-up foci as a control group, for a period of 12 weeks before re-introduction and for the same period in the previous year. Using field data and analytic hierarchical process (AHP), each variable and its sub-categories were weighted, and by calculating geometric means for each sub-category, score of corresponding cells of interaction matrices, lower and upper threshold of different risks strata, including low and mild risk of re-introduction and moderate and high risk of malaria outbreaks, were determined. The developed predictive model was calibrated through resampling with different sets of explanatory variables using R software. Sensitivity and specificity of the model were calculated based on new samples. Results: Twenty explanatory predictive variables of malaria re-introduction were identified and a predictive model was developed. Unpermitted immigrants from endemic neighbouring countries were determined as a pivotal factor (AHP score: 0.181). Moreover, quality of population movement (0.114), following malaria transmission season (0.088), average daily minimum temperature in the previous 8 weeks (0.062), an outdoor resting shelter for vectors (0.045), and rainfall (0.042) were determined. Positive and negative predictive values of the model were 81.8 and 100 %, respectively. Conclusions: This study introduced a new, simple, yet reliable model to forecast malaria re-introduction and outbreaks eight weeks in advance in pre-elimination and elimination settings. The model incorporates comprehensive deterministic factors that can easily be measured in the field, thereby facilitating preventive measures.