Mapping the spatial disparities of HIV prevalence in Ethiopian zones using the generalized additive model.

HIV is a worldwide social and health pandemic that poses a significant problem. This study contributes to the 2030 global agenda of reducing HIV prevalence. The study analyzed HIV prevalence using the 2016 Ethiopian Demographic and Health Survey data. The study included men aged 15-54 years and women aged 15-49 years who responded to questions about HIV tests. A generalized geo-additive model (GAM) was fitted to HIV data using nonparametric smooth terms for geolocations. Two smoothing techniques were used in GAMs to evaluate spatial disparities and the probable effects of variables on HIV risk. There were certain areas in Ethiopia that were identified as hot spot zones for HIV, including Nuer and Agnuak in Gambella, West Wollega and Illubabor in Oromia, Benchi Maji and Shaka in SNNPR, Awsi, Fantana, Kilbet, and Gabi in the Afar region, Shinilie of the Somalia region, North and South Wollo, Oromia special zones of the Amhara region, Central Ethiopia, and Addis Ababa city. On the other hand, the eastern parts of Ethiopia, particularly most zones in the Somalia region, were identified as cold spot zones with the lowest HIV odds ratio. The odds of HIV+ were higher for those who reside in rural areas than in urban areas. Furthermore, people who have STIs, who used contraceptive methods, and who learned at the secondary level of education were more likely to be infected with HIV. After adjusting for confounding variables, the results indicated that there are substantially significant spatial variations in HIV prevalence across Ethiopian zones. These results provide essential information to strategically target geographic areas to allocate resources and policy interventions at zonal level administrations.

Spatial multilevel analysis of age at death of under-5 children and associated determinants: EDHS 2000-2016.

OBJECTIVE: This study examines trends, spatial distribution and determinants of age at death of under-5 children in Ethiopia. DESIGN: This study used secondary data from the 2000, 2005, 2011 and 2016 Ethiopian Demographic and Health Surveys. A multilevel partial ordinal logistic regression model was used to assess the effects of variables on the age at death of children under 5 years. SETTING: Ethiopia. PARTICIPANTS: The final analysis included a sample of 3997 deaths of newborns, infants and toddlers. RESULTS: A total of 1508, 1054, 830 and 605 deaths of under-5 children were recorded in the 2000, 2005, 2011 and 2016 survey years, respectively. The death of newborns, infants and toddlers showed a significant decrease from 2000 to 2016, with reductions of 33.3% to 17.4%, 42.4% to 12.6% and 45.2% to 11.6%, respectively. The analysis using Global Moran's Index revealed significant spatial autocorrelation in mortality for each survey year (p<0.05). The intraclass correlation of age at death of under-5 children within regions was substantial. Furthermore, the odds of newborn deaths among under-5 children (OR: 0.638, 95% CI: 0.535, 0.759) were lower for those delivered in health institutions compared with those delivered at home. CONCLUSIONS: Throughout the survey years from 2000 to 2016, newborn children had higher mortality rates compared with infants and toddlers, and significant spatial variations were observed across different zones in Ethiopia. Factors such as child's sex, age of mother, religion, birth size, sex of household head, place of delivery, birth type, antenatal care, wealth index, spatial autocovariate, Demographic and Health Survey year, place of residence and region were found to be significant in influencing the death of under-5 children in Ethiopia. Overall, there has been a decreasing trend in the proportion of under-5 child mortality over the four survey years in Ethiopia.

Predictors of Viral Load and Medication Adherence Among HIV-Positive Adults Under Treatment at Felege-Hiwot Comprehensive Specialized Hospital, North-West, Ethiopia.

Background: Maintaining good medication adherence and decreasing viral load in patients living with HIV/AIDS are critical to ensuring antiretroviral therapy's preventive and therapeutic benefits. The main objective of this study was to assess the predictors of viral load and medication adherence among HIV-positive adults under treatment at Felege Hiwot Comprehensive Specialized Hospital (FHCSH). Methods: A retrospective cohort study design was conducted from a random sample of 281 adult HIV-infected patients under treatment at FHCSH in northwest Ethiopia from June 2017 to June 2021. Separate GLMM was used in analysis of viral load and medication adherence, and joint mode was applied to fit those two outcomes jointly. The potential correlation of those two outcomes was linked by random intercepts. Information criteria (AIC and BIC) were used for model comparison and covariance structure selection. Results: The small standard error of significant predictors and significant correlation between viral load and medication adherence over time provide evidence for joint model selection. The correlation between viral load and medication adherence was -0.7688 (P-value=< 0.05), which indicates that the decrement of viral load tends to increase good medication adherence. Patient substance use, visit time, baseline CD4 cell, baseline hemoglobin, and the interaction of visit time by substance use were significantly associated with viral load and medication adherence jointly. Conclusion: The study revealed that substance user adult patients, patients with low baseline CD4 cells, and patients with low baseline hemoglobin were with high viral loads and poor medication adherence. Therefore, health officials and other concerned bodies should give special attention and high intervention to patients with low baseline hemoglobin; poor adherence and low baseline CD4 cell count.

Renal Safety of Long-term Tenofovir Disoproxil Fumarate Treatment in Patients With Chronic Hepatitis B.

Background: Data on renal safety of tenofovir disoproxil fumarate (TDF) treatment among individuals with chronic hepatitis B (CHB) are inconsistent. The current study aimed to assess the effect of long-term TDF treatment on renal outcomes in adult patients with CHB. Methods: From a CHB cohort in Ethiopia, we included 233 patients treated with TDF and 126 untreated controls. Levels of creatinine and creatinine clearance over time were described in patients with and without TDF treatment. Linear mixed effects models with a treatment × time interaction were used to investigate the effect of TDF on creatinine and creatinine clearance. In treated patients only, change in creatinine and creatinine clearance was estimated separately in the first year as compared with subsequent years via linear mixed effects models. Results: Median follow-up in the treated group was 51 months (IQR, 27-72), and 75% of patients were male (median age, 33 years; IQR, 26-40). Median follow-up in the untreated group was 69 months (IQR, 66-72), and 48% of participants were male (median age, 33 years; IQR, 27-41). We found no change in creatinine over time in TDF-treated patients as compared with a slight increase in untreated patients (P interaction = .003). There was a decrease in creatinine clearance over time in both groups, which was stronger in patients without TDF treatment (P interaction = .007). In TDF-treated patients, changes in creatinine and creatinine clearance occurred mainly within the first 12 months after treatment initiation. Conclusions: This study showed no evidence of long-term renal toxicity of TDF treatment in patients with CHB.

Determinants of Time-to-Death of Chronic Lymphocytic Leukemia Patients at Felege Hiwot Referral Hospital, Bahir Dar, Ethiopia.

Background: Leukemia is a group of cancers that usually begin in the bone marrow and results in a large number of abnormal white blood cells. Chronic Lymphocytic Leukemia is the most prevalent leukemia in Western countries, with an estimated incidence rate of less than 1 to 5.5 per 100 000 people, and average age at diagnosis of 64 to 72 years. It is more common in men among Chronic Lymphocytic Leukemia patients in Ethiopia's hospitals at Felege Hiwot Referal Hospital. Methods: A retrospective cohort research design was employed to acquire critical information from patients' medical records in order to achieve the study's purpose. The study comprised the medical records of 312 Chronic Lymphocytic Leukemia who were followed from January 1, 2018 to December 31, 2020. A Cox proportional hazard model was used to determine the risk factors for time to death in Chronic Lymphocytic Leukemia patients. Results: Accordingly the Cox proportional hazard model, age (Hazard Ratio = 11.36; P < .001), sex of male (Hazard Ratio = 1.04; P = .004), married status (Hazard Ratio = 0.03; P = .003), medium stages of Chronic Lymphocytic Leukemia (Hazard Ratio = 1.29; P = .024), high stages of Chronic Lymphocytic Leukemia (Hazard Ratio = 1.99; P < .001), presence of anemia (Hazard Ratio =0.09; P = .005), platelets (Hazard Ratio = 2.11; P = .007), hemoglobin (Hazard Ratio = 0.02; P < .001), lymphocytes (Hazard Ratio = 0.29; P = .006), red blood cell (Hazard Ratio = 0.02; P < .001), which patients with Chronic Lymphocytic Leukemia had a significant relationship with time to death. Conclusions: Age, sex, Chronic Lymphocytic Leukemia stage, anemia, platelets, hemoglobin, lymphocytes, and red blood cells were all statistically significant determinants in the time to death of Chronic Lymphocytic Leukemia patients, according to the data. As a result, healthcare providers should pay particular attention to and emphasize the identified characteristics, as well as provide frequent counseling on how to enhance the health of Chronic Lymphocytic Leukemia patients.

Linear mixed model to identify the relationship between grain yield and other yield related traits and genotype selection for sorghum.

Sorghum is the most popular crop in arid and semi-arid areas, especially in Sub-Saharan African countries. Genotype effects, environmental and the interaction of genotype by environmental factors have an influence on phenotypic traits. The aim of the study is to identify the relationship between grain yield and other yield-related traits and select the genotypes which perform better in grain yield as well as to examine the association between the uncorrelated phenotypic traits and grain yield via mixed model. The data was generated using a lattice square design. Principal component analysis was used to generate uncorrelated variables for the mixed model. The study revealed that there was a difference in grain yield due to the treatment and there was a pairwise relationship among the phenotypic variables. 77.12% of the total variance of the original phenotypic variables was explained by the first three principal components and decided to use PCAs as input variables for the mixed model. All PCs had significant effects on grain yield as well as grain yield variability due to random effects associated with genotypes, genotype interaction by treatment, and replication within the treatment. The variability of grain yield due to genotype effect was explained about 45.73%, the variation of grain yield due to the interaction of genotype by the treatment was also explained about 39.06% and 1.55% of the variation of grain was explained by replication within treatment. The best performer genotypes recommended for mass production were G40 (Genotype 40), G186 (Genotype 186) and G196 (Genotype 196) without any constraint of environment. The genotypes recommended for mass production under irrigation conditions were G40 (Genotype 40), G62 (Genotype 62) and G192 (Genotype 192). G26 (Genotype 26), G55 (Genotype 55) and G49 (Genotype 49) were the genotypes recommended for mass production under stress conditions. Overall, the study recommends using a mixed model to fit the grain yield, and future work will focus on to evaluate the performance of genotypes under different environments and years of production.

Dynamic predictions from longitudinal CD4 count measures and time to death of HIV/AIDS patients using a Bayesian joint model.

A Bayesian joint modeling approach to dynamic prediction of HIV progression and mortality allows individualized predictions to be made for HIV patients, based on monitoring of their CD4 counts. This study aims to provide predictions of patient-specific trajectories of HIV disease progression and survival. Longitudinal data on 254 HIV/AIDS patients who received ART between 2009 and 2014, and who had at least one CD4 count observed, were employed in a Bayesian joint model of disease progression. Different forms of association structure that relate the longitudinal CD4 biomarker and time to death were assessed; and predictions were averaged over the different models using Bayesian model averaging. The individual follow-up times ranged from 1 to 120 months, with a median of 22 months and IQR 7-39 months. The estimates of the association structure parameters from two of the three models considered indicated that the HIV mortality hazard at any time point is associated with the rate of change in the underlying value of the CD4 count. Model averaging the dynamic predictions resulted in only one of the hypothesized association structures having non-zero weight in almost all time points for each individual, with the exception of twelve patients, for whom other association structures were preferred at a few time points. The predictions were found to be different when we averaged them over models than when we derived them from the highest posterior weight model alone. The model with highest posterior weight for almost all time points for each individual gave an estimate of the association parameter of -0.02 implying that for a unit increase in the CD4 count, the hazard of HIV mortality decreases by a factor (hazard ratio) of 0.98. Functional status and alcohol intake are important contributing factors that affect the mean square root of CD4 measurements.

Determining factors associated with cholera disease in Ethiopia using Bayesian hierarchical modeling.

BACKGROUND: Cholera is a diarrheal disease caused by infection of the intestine with the gram-negative bacteria Vibrio cholera. It is caused by the ingestion of food or water and infected all age groups. This study aimed at identifying risk factors associated with cholera disease in Ethiopia using the Bayesian hierarchical model. METHODS: The study was conducted in Ethiopia across regions and this study used secondary data obtained from the Ethiopian public health institute. Latent Gaussian models were used in this study; which is a group of models that contains most statistical models used in practice. The posterior marginal distribution of the Latent Gaussian models with different priors is determined by R-Integrated Nested Laplace Approximation. RESULTS: There were 2790 cholera patients in Ethiopia across the regions. There were 81.61% of patients are survived from cholera outbreak disease and the rest 18.39% have died. There was 39% variation across the region in Ethiopia. Latent Gaussian models including random and fixed effects with standard priors were the best model to fit the data based on deviance. The odds of surviving from cholera outbreak disease for inpatient status are 0.609 times less than the outpatient status. CONCLUSIONS: The authors conclude that the fitted latent Gaussian models indicate the predictor variables; admission status, aged between 15 and 44, another sick person in a family, dehydration status, oral rehydration salt, intravenous, and antibiotics were significantly associated with cholera outbreak disease.

Prevalence and associated factors of neonatal mortality in Ethiopia.

Neonatal mortality is the death of a live-born baby within the first 28 days of birth. For the selected households, neonatal mortality was collected from children aged 0-28 days and women aged 15-49. The neonatal period is a significant 4-week period in human life because it carries a greater mortality risk. To identify the determinant factors of neonatal mortality in Ethiopia based on EDHS 2016 data with the application of count regression models. In this study, all neonates in Ethiopia were born within the 5 years preceding EDHS 2016 of the source population in the selected EAs from September to December 2015. Count regression models were used to analyze the data. A total of 10,641 live-born neonates within the previous 5 years of EDHS 2016 had neonatal mortality of women aged 15-49, which was considered in the study to be 7193. The data were found to have excess zeros (96.6%), and the variance (0.052) was higher than its mean (0.04). The count regression model (ZINB) was best fitted to the data with maximum likelihood parameter estimation methods. The average neonatal mortality difference in multiple births was increased by IRR = 8.53 times compared with a single birth. The average number of neonatal deaths experienced during breastfeeding was lower (IRR = 0.38) than that experienced by mothers who did not experience breastfeeding their child. The average neonatal mortality difference in rural residences was increased by IRR = 3.99 times compared to urban mothers' residences. In this study, the prevalence of Neonatal mortality in Ethiopia was higher. For selected ZINB count regression models of explanatory variables, such as multiple birth types, having rural residence factors of neonatal mortality increased the risk of death. However, having early breastfeeding, a female household head, and antenatal visits (1-4) and (5-10) during pregnancy decrease the risk of neonatal death.

Risk Factors of White Blood Cell Progression Among Patients With Chronic Lymphocytic Leukemia at Felege Hiwot Referral Hospital, Bahir Dar, Ethiopia.

BACKGROUND: Leukemia is a type of cancers that start in the bone marrow and produce a serious number of abnormal white blood cells. Bleeding and bruising problems, fatigue, fever, and an increased risk of infection are among symptoms of the disease. The main objective of this study is to identify the determinant of the progression rate of white blood cells among patients with chronic lymphocytic leukemia at Felege Hiwot Referral Hospital (FHRH), Bahir Dar, Ethiopia. METHODS: A retrospective study design was conducted on 312 patients with chronic lymphocytic leukemia at FHRH, Bahir Dar, Ethiopia under treatment from 1 January 2017 to 31 December 2019. A linear mixed-effects model was considered for the progression of the white blood cell data. RESULTS: The estimated coefficient of the fixed effect intercept was 84.68, indicating that the average white blood cell (WBC) count of the patients was 84.68 at baseline time by excluding all covariates in the model (P-value <.001). Male sex (ß = 2.92, 95% confidence interval [CI] 0.58, 0.5.25), age (ß = .17, 95% CI 0.08, 0.28), widowed/divorced marital status (ß = 3.30, 95% CI 0.03, 6.57), medium chronic lymphocytic leukemia (CLL) stage (ß = -4.34, 95% CI -6.57, -2.68), high CLL stage (ß = -2.76, 95% CI -4.86, -0.67), hemoglobin (ß = .15, 95% CI 0.07, 0.22), platelet (ß = .09, 95% CI 0.02, 0.17), lymphocytes (ß = .16, 95% CI 0.03, 0.29), red blood cell (RBC) (ß = .17, 95% CI 0.09, 0.25), and follow-up time (ß = .27, 95% CI 0.19, 0.36) were significantly associated with the average WBC count of chronic lymphocytic leukemia patients. CONCLUSIONS: The finding showed that age, sex, lymphocytic, stage of chronic lymphocytic leukemia, marital status, platelet, hemoglobin, RBC, and follow-up time were significantly associated with the average WBC count of chronic lymphocytic leukemia patients. Therefore, health care providers should give due attention and prioritize those identified factors and give frequent counseling about improving the health of chronic lymphocytic leukemia patients.

Predictors for time to recovery from sever acute malnutrition among under-five children admitted to therapeutic feeding unit at Dubti referral hospital, Afar region, Ethiopia.

BACKGROUND: Currently, about 165 million children are categorized under malnutrition and 51.5 million suffering from acute malnutrition in world wide. Hence, the objective of current study was to assess the recovery time and its predictors of children under five from severe acute malnutrition admitted to Therapeutic Feeding Unit at Dubti Referral Hospital, Afar region, Eastern Ethiopia. METHODS: Institutional based retrospective cohort study was conducted on 650 inpatient children with SAM admitted for therapeutic feeding unit whose treatment was from March to April/2017. RESULTS: The result in current investigation indicates that the average recovery time from SAM was found to be 21 days (95% CI; 21.23-25.77), p-value = 0.035). A Cox proportional hazard regression model revealed that Weight of a child at birth, gestational age of a child, working status of a child at admission birth order of a child, mother's BMI, mother's level of education, mother's stature, mother's occupation, mother's age, mother's marital status, mother's nutritional status, house hold income in ETB, family size in HH, number of under-five children, the type of toilet used in HH, source of improved drinking water, type of cooking fuel, ownership of livestock, age and weight of a child at admission had statistically significant association with the variation of average recovery time of children from SAM. CONCLUSION: Male children under severe acute malnutrition, rural children, children with different additional diseases and children who did not get mothers' breast milk at least in the first six months after birth and children who did not get vaccination are groups at risk and needs intervention and special attention to be recovered with short period of time. Children from low income family, who did not get improved drinking water, without moderate cooking fuel and a child from larger families were groups at risk in recovery time from SAM.

Malaria vector dynamics and utilization of insecticide-treated nets in low-transmission setting in Southwest Ethiopia: implications for residual transmission.

BACKGROUND: Understanding the behaviour of local malaria vectors is essential as effectiveness of the commonly used vector-targeted malaria control tools heavily relies on behaviour of the major malaria vectors. This study was conducted to determine species composition, biting behaviour, host preference and infectivity of anopheline mosquitoes, and assess utilization of insecticide-treated nets (ITNs) in a low transmission setting in Southwest Ethiopia. METHODS: Adult anopheline mosquitoes were collected using human landing catches (HLCs), Centers for Disease Control and Prevention (CDC) light traps (LTs) and Pyrethrum Spray Catches (PSCs) from June 2016 to May 2018 in Kishe, Jimma Zone, Southwest Ethiopia. The anopheline mosquitoes were morphologically identified. Moreover, sub-sample of An. gambiae s.l. was identified to species using polymerase chain reaction (PCR). Circum-sporozoite proteins (CSPs) and blood meal sources of the anopheline mosquitoes were tested using enzyme-linked immunosorbent assay (ELISA). In addition, a cross-sectional survey was conducted to assess ITN utilization by the inhabitants. RESULTS: A total of 3659 anopheline mosquitoes comprising An. coustani complex (84.4%), An. gambiae s.l. (11.3%), and An. pharoensis and An. squamosus comprising less than 5% were collected. The anopheline mosquitoes showed marked outdoor (67%) and early evening (63%) biting behaviour. An. coustani complex and An. gambiae s.l. were predominantly zoophilic and anthropophilic, respectively. None of the sampled anopheline were CSP-positive. Most of the households (97.8%) owned at least one ITN, with modest usage by the inhabitants (73.4%). ITN usage was significantly higher among under-five children (AOR = 7.9, 95% CI: 4.41-14.03), household heads and spouses (AOR = 4.8, 95% CI: 3.0-7.59), those with sufficient access to ITNs (AOR = 1.8, 95% CI: 1.39-2.35), and who were not utilizing alternative mosquito repellents (AOR = 2.2, 95% CI: 1.58-2.99). CONCLUSION: The anopheline mosquito species exhibited predominantly outdoor and early evening biting activity. Household ITN coverage was high with slight gap in usage. Vector control interventions should target outdoor and early biting vectors to further suppress the local mosquito population. Moreover, sensitization of the community on consistent use of ITNs is required.

Associated risk factors of underweight among under-five children in Ethiopia using multilevel ordinal logistic regression model.

BACKGROUND: Malnutrition is associated with both under nutrition and over nutrition which causes the body to get improper amount of nutrients to maintain tissues and organ function. Under nutrition is the result of insufficient intake of food, poor utilization of nutrients due to illnesses, or a combination of these factors. The purpose of this study was to identify associated risk factors and assess the variation of underweight among under-five children of different regions in Ethiopia. METHODS: Ethiopian Demography and Health Survey (EDHS-2016) weight-to-age data for under-five children is used. In order to achieve the objective of this study; descriptive, single level and multilevel ordinal logistic regression analysis were used. RESULTS: From a total of 8935 children about 8.1% were severely underweight, 17.1% were moderately underweight and 74.8% were normal. The test of heterogeneity suggested that underweight varies among region and multilevel ordinal model fit data better than single level ordinal model. CONCLUSION: Educational level of mother, religion, birth order, type of birth, sex of child, mother body mass index, birth size of child, existence of diarrhea for last two weeks before survey, existence of fever for last two weeks before survey, duration of breast feeding, age child and wealth index had significant effect on underweight among under-five children in Ethiopia. The finding revealed that among the fitted multilevel partial proportional odds model, the random intercept model with fixed coefficients is appropriate to assess the risk factors of underweight among under-five children in Ethiopia. The findings of this study have important policy implications. The government should work closely with both the private sector and civil society to teach women to have sufficient knowledge, awareness and mechanisms of improving under-five underweight for children's wellbeing.

Modeling successive birth interval of women in Ethiopia: application of parametric shared frailty and accelerated failure time model.

BACKGROUND: Both short and long birth intervals are associated with many risk factors and about 29% of births are short birth intervals in Ethiopia. The purpose of this study is to model the birth intervals of adult women aged 15-49 years using accelerated failure time and shared frailty models in order to analyze the birth intervals of Ethiopian women. METHODS: The data was obtained from the 2016 Ethiopian Demographic and Health Survey (EDHS). Accelerated failure time with different baseline and shared frailty models are used for the analysis to identify important demographic and socio-economic factors affecting the length of birth intervals and correlates of the birth intervals respectively. RESULTS: The data consists of 9147 women, of which about 7842 (85.5%) are closed interval and the rest of 1323(14.5%) are open interval. Accelerated failure time (AFT) result revealed that women education level, husbands education level, age at first birth, marital status, religion and family wealth index are significant factors affecting birth interval of women in Ethiopia. CONCLUSION: Women with closely spaced births tend to have larger family sizes when compared with women with longer inter-birth interval. Longer successive birth interval tends to reduce the total fertility rate of women. Furthermore, improvements in socio-economic status and level of education of women associate with reduced fertility, improved maternal and child wellbeing, and longer birth interval.

Bayesian model with application to a study of dental caries.

BACKGROUND: Dental caries are a significant public health problem. It is a disease with multifactorial causes. In Sub-Sahara Africa, Ethiopia is one of the countries with a high record of dental caries. This study was to determine the risk factors affecting dental caries using both Bayesian and classical approaches. METHODS: The study design was a retrospective cohort study in the period of March 2009 to March 2013 dental caries patients Hawassa Haik Poly Higher Clinic. The Bayesian logistic regression procedure was adapted to make inference about the parameters of a logistic regression model. The purpose of this method was generating the posterior distribution of the unknown parameters given both the data and some prior density for the unknown parameters. RESULTS: From this study the prevalence of natural dental caries was 87% and non-natural dental caries were 13%. The age group of 18-25 was higher prevalence of dental caries than the other age groups. From Bayesian logistic regression, we found out that rural patients, do not clean their teeth, patients from SNNPR and age group 18-25 are statistically significant. The finding from the Bayesian statistics approach is getting popular in data analysis than classical statistics because the technique is more robust and precise. CONCLUSIONS: Bayesian approach was found to be better than classical method as the value of the standard errors in Bayesian approaches is smaller than that of classical logistic regression. The Bayesian credible interval is smaller than the length of the confidence interval for all significant risk factors. Age, sex, place of residence, region and habit of cleaning teeth was found to have a significant effect on dental caries patients.

Joint Bayesian modeling of time to malaria and mosquito abundance in Ethiopia.

BACKGROUND: This paper studies the effect of mosquito abundance and malaria incidence in the last 3 weeks, and their interaction, on the hazard of time to malaria in a previously studied cohort of children in Ethiopia. METHODS: We model the mosquito abundance and time to malaria data jointly in a Bayesian framework. RESULTS: We found that the interaction of mosquito abundance and incidence plays a prominent role on malaria risk. We quantify and compare relative risks of various factors, and determine the predominant role of the interaction between incidence and mosquito abundance in describing malaria risk. Seasonal rain patterns, distance to a water source of the households, temperature and relative humidity are all significant in explaining mosquito abundance, and through this affect malaria risk. CONCLUSION: Analyzing jointly the time to malaria data and the mosquito abundance allows a precise comparison of factors affecting the spread of malaria. The effect of the interaction between mosquito abundances and local presence of malaria parasites has an important effect on the hazard of time to malaria, beyond abundance alone. Each additional one km away from the dam gives an average reduction of malaria relative risk of 5.7%. The importance of the interaction between abundance and incidence leads to the hypothesis that preventive intervention could advantageously target the infectious population, in addition to mosquito control, which is the typical intervention today.