Two new malaria articles

Our malaria research group recently published two new articles about malaria in south Ethiopia:

Massebo F, Balkew M, Gebre-Michael T, Lindtjorn B. Entomologic Inoculation Rates of Anopheles arabiensis in Southwestern Ethiopia. Am J Trop Med Hyg 2013.

Woyessa A, Deressa W, Ali A, Lindtjørn B. Malaria risk factors in Butajira area, south-central Ethiopia: a multilevel analysis. Malaria Journal 2013, 12:273. 

Model to validate species distribution and seasonal variation

This article is a validation of a mathematical model described earlier.Overall, the model gives a realistic representation of seasonal and year-to-year variability in mosquito densities and it can accurately predict the distribution of An. gambiae s.s. and An. arabiensis in sub-Saharan Africa. It may be used for seasonal and long-term predictions of changes in the burden of malaria.

Lunde TM, Balkew M, Korecha D, Gebre-Michael T, Massebo F, Sorteberg A and Lindtjørn B. A dynamic model of some malaria-transmitting anopheline mosquitoes of the Afrotropical region. II. Validation of species distribution and seasonal variations. Malaria Journal 2013, 12:78

Background  The first part of this study aimed to develop a model for Anopheles gambiae s.l. with separate parametrization schemes for Anopheles gambiae s.s. and Anopheles arabiensis. The characterizations were constructed based on literature from the past decades. This part of the study is focusing on the model’s ability to separate the mean state of the two species of the An. gambiae complex in Africa. The model is also evaluated with respect to capturing the temporal variability of An. arabiensis in Ethiopia. Before conclusions and guidance based on models can be made, models need to be validated.

Methods  The model used in this paper is described in part one (Malaria Journal 2013, 12:28). For the validation of the model, a data base of 5,935 points on the presence of An. gambiae s.s. and An. arabiensis was constructed. An additional 992 points were collected on the presence An. gambiae s.l.. These data were used to assess if the model could recreate the spatial distribution of the two species. The dataset is made available in the public domain. This is followed by a case study from Madagascar where the model’s ability to recreate the relative fraction of each species is investigated. In the last section the model’s ability to reproduce the temporal variability of An. arabiensis in Ethiopia is tested. The model was compared with data from four papers, and one field survey covering two years.

Results  Overall, the model has a realistic representation of seasonal and year to year variability in mosquito densities in Ethiopia. The model is also able to describe the distribution of An. gambiae s.s. and An. arabiensis in sub-Saharan Africa. This implies this model can be used for seasonal and long term predictions of changes in the burden of malaria. Before models can be used to improving human health, or guide which interventions are to be applied where, there is a need to understand the system of interest. Validation is an important part of this process. It is also found that one of the main mechanisms separating An. gambiae s.s. and An. arabiensis is the availability of hosts; humans and cattle. Climate play a secondary, but still important, role.

Malaria model

This study highlights some of the assumptions commonly used when constructing mosquito-malaria models and presents a realistic model of Anopheles gambiae s.s. and Anopheles arabiensis, and their interaction.

We make a case that this new mosquito model, OMaWa, may improve the understanding of vector dynamics, which in turn can be used to better understand the dynamics of malaria.

Lunde TM, Korecha D, Loha E, Sorteberg A and Lindtjørn B. A dynamic model of some malaria-transmitting anopheline mosquitoes of the Afrotropical region. I. Model description and sensitivity analysis. Malaria Journal 2013, 12:28

Background: Most of the current biophysical models designed to address the large-scale distribution of malaria assume that transmission of the disease is independent of the vector involved. Another common assumption in these type of model is that the mortality rate of mosquitoes is constant over their life span and that their dispersion is negligible. Mosquito models are important in the prediction of malaria and hence there is a need for a realistic representation of the vectors involved.

Results: We construct a biophysical model including two competing species, Anopheles gambiae s.s. and Anopheles arabiensis. Sensitivity analysis highlight the importance of relative humidity and mosquito size, the initial conditions and dispersion, and a rarely used parameter, the probability of finding blood. We also show that the assumption of exponential mortality of adult mosquitoes does not match the observed data, and suggest that an age dimension can overcome this problem.

Conclusions: This study highlights some of the assumptions commonly used when constructing mosquito-malaria models and presents a realistic model of An. gambiae s.s. and An. arabiensis and their interaction. This new mosquito model, OMaWa, can improve our understanding of the dynamics of these vectors, which in turn can be used to understand the dynamics of malaria.

How bednets and indoor residual spraying influence spatio-temporal clustering of malaria

Loha E, Lunde TM, Lindtjørn B. Effect of Bednets and Indoor Residual Spraying on Spatio-Temporal Clustering of Malaria in a Village in South Ethiopia: A Longitudinal Study. PLoSONE 2012; 7(10): e4735.


Understanding 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.


A 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.


The 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 spacetime 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.


The 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.


(This paper was also been presented at a conference that BioMed Central, in conjunction with its journals Malaria Journal and Parasites & Vectors, hosted. The second malaria conference “Challenges in Malaria Research: Progress Towards Elimination” was held in Basel, Switzerland from 10 – 12 October 2012).

Malaria incidence in south Ethiopia

We have now published the large malaria incidence study from Arba Minch: Loha E, Lindtjorn B. Predictors of Plasmodium falciparum Malaria Incidence in Chano Mille, South Ethiopia: A Longitudinal Study. Am J Trop Med Hyg. 2012. You find the publication at


We assessed potential effects of local meteorological and environmental conditions, indoor residual spray with insecticides, insecticide-treated nets (ITNs) use at individual and community levels, and individual factors on Plasmodium falciparum malaria incidence in a village in south Ethiopia. A cohort of 8,121 people was followed for 101 weeks with active and passive surveillance. Among 317 microscopically confirmed P. falciparum malaria episodes, 29.3% occurred among temporary residents. The incidence density was 3.6/10,000 person-weeks of observation. We observed higher malaria incidence among males, children 5–14 years of age, ITNs non-users, the poor, and people who lived closer to vector breeding places. Rainfall increased and indoor residual spraying with Deltamethrin reduced falciparum incidence. Although ITNs prevented falciparum malaria for the users, we did not find that free mass ITNs distribution reduced falciparum malaria on a village level.

Malaria mosquito larvae in the highlands of south-central Ethiopia

This study shows that streams serve as the main breeding sites of anopheline mosquitoes in the Butajira area of south-central Ethiopia. Density of larvae of An. arabiensis, the main malaria vector in the country, was highest along the Odamo stream (1817 m altitude) and decreased significantly along the streams with increasing altitude.

The following text contains the abstract of the article:

Abebe Animut, Teshome Gebre-Michael, Meshesha Balkew and Bernt Lindtjørn. Abundance and dynamics of anopheline larvae in a highland malarious area of south-central EthiopiaParasites & Vectors 2012, 5:117 doi:10.1186/1756-3305-5-117

Background: Malaria is a public health problem in Ethiopia, and increasingly so in highland areas, possibly because of global warming. This study describes the distribution, breeding habitat and monthly dynamics of anopheline larvae in Butajira, a highland area in south-central Ethiopia.

Methods: A study of the abundance and dynamics of Anopheles larvae was undertaken at different sites and altitudes in Butajira from July 2008 to June 2010. The sites included Hobe (1817m.a.s.l), Dirama (1995m.a.s.l.) and Wurib (2196m.a.s.l.). Potential anopheline larval habitats were surveyed once per month in each village. The recorded characteristics of the habitats included habitat type, pH, surface debris, emergent plants, algae, substrate, turbidity, temperature, length, width, depth, distance to the nearest house and anophelines. The Spearman correlation coefficient and Mann-Whitney U test were used to calculate the degree of association between the density of anopheline species and key environmental factors.

Results: Among the different types of habitat surveyed, the Odamo, Akamuja and Assas streams and Beko swamp were positive for anopheline larvae. A total of 3,957 third and fourth instar larvae were collected from the three localities, and they represented ten species of anophelines. These were: Anopheles cinereus (32.5%), An. arabiensis (31.4%), An. chrysti (23%), An. demeilloni (12.2%), An. pretoriensis (0.6%), An. azaniae (0.1%), An. rufipes(0.1%), An. sergentii (0.06%), An. garnhami (0.06%) and An. pharoensis (0.03%). The density of anopheline larvae was highest during the dry months. An. arabiensis was widely distributed, and its density decreased from the lowest elevation in Hobe to the highest in Wurib. The density of An. arabiensis larvae was correlated positively with larval habitat temperature (r = 0.33, p < 0.05) and negatively with depth of larval habitat (r = 0.56, p < 0.05).

Conclusion: Ten species of anophelines were identified, including two known vectors of malaria (An. arabiensis and An. pharoensis), along streams in Butajira. Larvae of An. arabiensis were found in streams at 2200m.a.s.l. This possible expansion of the malaria vector to highland areas indicates an increasing risk of malaria because a large proportion of the Ethiopian population live above this altitude.

Forecasting Malaria

On March 30, Kjersti Brown from SIU presented our malaria research in Ethiopia:

Researchers from Ethiopia and Norway have developed a new model for forecasting malaria epidemics.

Climate change is presenting major challenges in Africa. Malaria, one of the big killers of African children, is a disease directly linked to temperature and rainfall. In Ethiopia, malaria occurs seasonally. Every four to six years there are huge epidemics, affecting as many as several hundred thousand people. Global warming now seems to be changing the pattern of malaria. Will high-land Ethiopia experience more malaria in the future? And if so, will it be possible to predict epidemics in time for people to prepare?


You can read the full presentation here.