Background: The concept of food insecurity encompasses three dimensions. One of these dimensions, the access component of household food insecurity is measured through the use of the Household Food Insecurity Access Scale (HFIAS). Despite its application in Ethiopia and other similar developing countries, its performance is still poorly explored. Our study aims to evaluate the validity of the HFIAS in Ethiopia. Methods: We conducted repeated cross-sectional studies in urban and rural villages of the Butajera District in southern Ethiopia. The validation was conducted on a pooled sample of 1,516 households, which were selected using a simple random sampling method. The HFIAS was translated into the local Amharic language and tested for face validity. We also evaluated the tool's internal consistency using Cronbach's alpha and factor analysis. We tested for parallelism on HFIAS item response curves across wealth status and further evaluated the presence of a dose-response relationship between the food insecurity level and the consumption of food items, as well as between household wealth status and food insecurity. Additionally, we evaluated the reproducibility of the tool through the first and second round of HFIAS scores. Results: The HFIAS exhibited a good internal consistency (Cronbach's alpha for the values of rounds 1 and 2 were 0.76 and 0.73, respectively). A factor analysis (varimax rotation) resulted in two main factors: the first factor described a level of mild to moderate food insecurity, while the second factor described severe food insecurity. HFIAS item response curves were parallel across wealth status in the sample households, with a dose-response trend between food insecurity levels and the likelihood of previous day food consumption being observed. The overall HFIAS score did not change over the two rounds of data collection. Conclusions: The HFIAS is a simple and valid tool to measure the access component of household food insecurity. However, we recommend the adaptation of questions and wordings and adding examples before application, as we found a discrepancy in understanding of some of the nine HFIAS questions.

BackgroundIt is well known that temperature has a major influence on the transmission of malaria parasites to their hosts. However, mathematical models do not always agree about the way in which temperature affects malaria transmission.MethodsIn this study, we compared six temperature dependent mortality models for the malaria vector Anopheles gambiae sensu stricto. The evaluation is based on a comparison between the models, and observations from semi-field and laboratory settings.ResultsOur results show how different mortality calculations can influence the predicted dynamics of malaria transmission.ConclusionsWith global warming a reality, the projected changes in malaria transmission will depend on which mortality model is used to make such predictions.

BackgroundUnderstanding the spatio-temporal pattern of malaria transmission where prevention and control measures are in place will help to fine-tune strategies. The objective of this study was to assess the effect of mass distribution of bednets and indoor residual spraying (IRS) with insecticides on the spatio-temporal clustering of malaria in one malaria endemic village in south Ethiopia.MethodsA longitudinal study was conducted from April 2009 to April 2011. The average population was 6631 in 1346 locations. We used active and passive searches for malaria cases for 101 weeks. SatScan v9.1.1 was used to identify statistically significant retrospective space–time clusters. A discrete Poisson based model was applied with the aim of identifying areas with high rates. PASW Statistics 18 was used to build generalized Poisson loglinear model.ResultsThe total number of both types of malaria episodes was 622, giving 45.1 episodes per 1000 persons per year; among these, episodes of Plasmodium falciparum and vivax infection numbered 316 (22.9 per 1000 per year) and 306 (22.2 per 1000 per year), respectively. IRS with Dichlorodiphenyltrichloroethane (DDT) and later with Deltamethrin and free mass distribution of insecticide-treated nets (ITNs) were carried out during the study period. There was space–time clustering of malaria episodes at a household level. The spatio-temporal clustering of malaria was not influenced by free mass distribution of ITNs; however, the time-span of the spatio-temporal clustering of malaria cases ended after IRS with Deltamethrin. The presence of clusters on the south-east edge of the village was consistent with the finding of an increasing risk of acquiring malaria infection for individuals who lived closer to the identified vector breeding site.ConclusionThe risk of getting malaria infection varied significantly within one village. Free mass distribution of ITNs did not influence the spatio-temporal clustering of malaria, but IRS might have eliminated malaria clustering.