Objective:Families' perceptions, beliefs, and attitudes about malaria causation, symptom identification, treatment of malaria, and prevention are often overlooked in malaria control efforts. This study was conducted to understand these issues, which can be an important step towards developing strategies, aimed at controlling malaria.Materials and Methods:A community based descriptive cross-sectional study in four villages: Danwarai, Gehuru, Jiga, and Kashin Zama of Aliero local government area in Kebbi Sate, in northern Nigeria. Two hundred household were randomly selected and interviewed using standardized questionnaire.Results:Knowledge of the role of mosquitoes in malaria transmission (11.8%) and cause of malaria (9.6%) was observed to be low among the study population. Comprehensive knowledge about malaria prevention measures was high (90%), but not reflecting in their practice (16%). They have good knowledge of mosquito behavior (breeding areas (64.5%), resting places (70%) and biting time (81%)). Seeking hospital care for a febrile child was a good practice (68.5%) observed. Attitudes regarding the best antimalarial therapy was limited (56.7%) to chloroquine.Conclusions:Misconceptions about malaria transmission and its cause still exist. Knowledge about preventive measures does not necessarily translate into improvement in practices. There is a need for targeted educational programs to increase the communities' efforts to develop desirable attitude and practices regarding malaria and their participation for malaria control.

Background:Presumptive diagnosis of malaria is widespread, even where microscopy is available. As fever is very nonspecific, this often leads to over diagnosis, drug wastage and loss of opportunity to consider alternative causes of fever, hence the need to improve on the clinical diagnosis of malaria.Materials and Methods:In a prospective cross-sectional comparative study, we examined 45 potential predictors of uncomplicated malaria in 800 febrile children (0-12 years) in Sokoto, Nigeria. We developed a clinical algorithm for malaria diagnosis and compared it with a validated algorithm, Olaleye's model.Results:Malaria was confirmed in 445 (56%). In univariate analysis, 13 clinical variables were associated with malaria. In multivariate analysis, vomiting (odds ratio, OR 2.6), temperature ≥ 38.5°C (OR 2.2), myalgia (OR 1.8), weakness (OR 1.9), throat pain (OR 1.8) and absence of lung crepitations (OR 5.6) were independently associated with malaria. In children over age 3 years, any 3 predictors had a sensitivity of 82% and specificity of 47% for malaria. An Olaleye score ≥ 5 had a sensitivity of 62% and a specificity of 51%.Conclusion:In hyperendemic areas, the sensitivity of our algorithm may permit presumptive diagnosis of malaria in children. Algorithm positive cases can be presumptively treated, and negative cases can undergo parasitological testing to determine need for treatment.

This study aimed at enhancing the efficiency of Zaman estimators using exponential transformation technique. A new class of estimators was obtained using the concept of Bahl and Tuteja. The bias and mean squared error (MSE) of the new class of suggested estimators was derived up to second degree approximation. The empirical study through simulations was conducted using Normal, exponential, gamma, chi-square and beta distributions under robust regression methods (Huber-M, Huber-MM, LTS (least trimmed squares) and LMS (least median of squares)) and the results revealed that proposed estimators were more efficient. K E Y W O R D Sefficiency, exponential type estimators, robust regression, outliers INTRODUCTIONRatio, product and regression estimators had undergone series of modification and improvement by several authors using different techniques like power transformation, exponential transformation, linear combination and so forth. Bahl and Tuteja 5 were the first to utilize exponential transformation on ratio and product estimators and thereafter several authors like Singh and Audu, 15 Audu and Singh 4 , Muili et al. 9 , Ishaq et al. 7 , Audu et al. 3 , Singh et al. 14 , Olayiwola et al. 12 , Olayiwola et al. 11 and Audu et al. 2 have used similar approach to enhance the efficiency of estimators of population parameters. Similarly, supplementary variables associated with the study variables have been identified to be helpful in improving the efficiency of ratio, product and regression estimators both at planning and estimation stages. However, the efficiency of these estimators may be affected by data which are characterized by outliers or leverages. Some of the techniques for detecting outliers include Boxplot, Stem and Leaf plot, P-P plot, Euclidean distance, Mahalanobis distance, Hosmer and Lemeshow goodness-of-fit test, Cook's 𝐷 𝑖 . 1 To address the issue of outliers' effects, authors like Kadilar and Cingi 8 , Zaman and Bulut 18 and Zaman 19 have suggested several robust ratio estimators. The current study intends to utilize exponential transformation on Zaman 19 estimators to obtain new estimators with higher efficiency.Zaman and Bulut 18 extended the work of Kadilar and Cingi 8 by inclusion of some slopes' coefficient of other robust regression estimators like Tukey-M, 16 Hampel-M, 6 LMS 13 and LAD 10 in addition to Huber-M 20 used by Kadilar and Cingi 8 and this inclusion leads to new estimators of population mean in the presence of outliers as given below: