title: Predicting factors for malaria re-introduction: an applied model in an elimination setting to prevent malaria outbreaks.
abstract: 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.
authors.affiliation: Center for Vectors and Vector-Borne Diseases, Department of Biology, Mahidol University, Bangkok, Thailand. Mansourrk@gmail.com.|Independent Malaria Consultant, Member of Surveillance, Monitoring and Evaluation Technical Expert Group, Global Malaria Programme, WHO, Geneva, Switzerland. Mansourrk@gmail.com.
authors.forename: Mansour
authors.initials: M
authors.lastname: Ranjbar
authors.affiliation: Zanjan Social Determinants of Health Research Centre, Zanjan University of Medical Silences and Health Services, Zanjan, Iran. shoghli@yahoo.com.
authors.forename: Alireza
authors.initials: A
authors.lastname: Shoghli
authors.affiliation: Epidemiology Department, School of Public Health, Shahid Beheshti University of Medical Silences and Health Services, Tehran, Iran. gfarhood@gmail.com.
authors.forename: Goodarz
authors.initials: G
authors.lastname: Kolifarhood
authors.affiliation: Infectious Diseases and Tropical Medicine Research Center, School of Public Health, Zahedan University of Medical Sciences, I.R. of Iran, Zahedan, Iran. zu.healthdeputy@gmail.com.
authors.forename: Seyed Mehdi
authors.initials: SM
authors.lastname: Tabatabaei
authors.affiliation: Independent Malaria Consultant, Tehran, Iran. Amlashi@gmail.com.
authors.forename: Morteza
authors.initials: M
authors.lastname: Amlashi
authors.affiliation: Health Promotion Research Center, Zahedan University of Medical Sciences, Zahedan, Iran. memohammadi@yahoo.com.
authors.forename: Mahdi
authors.initials: M
authors.lastname: Mohammadi
mesh_terms: D019295:Computational Biology; D004196:Disease Outbreaks / Q000517:prevention & control* / Q000706:statistics & numerical data*; D006801:Humans; D007492:Iran / Q000453:epidemiology; D008288:Malaria / Q000453:epidemiology* / Q000517:prevention & control* / Q000635:transmission; D008962:Models, Theoretical; D018570:Risk Assessment