Household Expenditure on Treatment of Presumptive Malaria in a Rural Community of North-western Nigeria

Background: Malaria is endemic in Nigeria and there is a vicious cycle between it and poverty. It contributes towards poverty, while poverty influences the risk of its infection. Majority of Nigerians, 70%, live in rural areas, below poverty line. They earn less than $1.25 a day. Subsistence farming is their main occupation. The cost of malaria treatment represents a significant portion of their income.Objective: This study was conducted to assess the direct cost of presumptive malaria treatment on households in Gimba Village of Soba Local Government Area of Kaduna State, Nigeria.Methodology: A cross-sectional descriptive study conducted during community diagnosis posting of final year medical students of Ahmadu Bello University, Zaria in July 2012. An interviewer- administered questionnaire was used to collect data from household heads.Results: Most of the respondents (69.7%) were farmers. A large proportion of the respondents (47.3%) earned between N10,000.00 to N20,000.00. monthly. The average household size was 6 while the average number of presumptive malaria cases per household per year was 13. On average, the direct cost of presumptive malaria treatment alone, consumes 4.9 % of the annual income of household heads. There was a statistically significant association between cost of treatment and place of seeking treatment (p <0.001).Conclusion: The direct cost of presumptive malaria treatment alone consumed a large proportion of the meagre annual income of households in the study area. For effective malaria control in Nigeria, free or subsidized malaria treatment and rural health insurance scheme are recommended.Keywords: Household, expenditure, Treatment, presumptive malaria, Gimba Community, Nigeria

Occupational Hazards and HBV infection among health care workers in Public Teaching Hospitals in Khartoum State, Sudan: A multiple Discriminant Analysis

Background: Infection with HBV leads to a wide spectrum of liver injury. It ranges from acute self-limited infection and fulminant hepatitis to chronic hepatitis.Objectives: To examine the prevalence of sero-epidemiologic markers of hepatitis B virus and to identify the risk factors of exposure to HBV among health care workers in Public Teaching Hospitals in Khartoum State, Sudan; in 2004.Methods: The study was a cross sectional, facility-based study. It was conducted on stratified two stage cluster sampling of 843 subjects. The study adopted multivariate statistical approach, using Multiple Discriminant Analysis (MDA) and some non-parametric tests.Results: Infection rate measured by Anti-HB core, carrier rate measured by HBs Ag, and a profile of high infectivity rate measured by HBe Ag was found to be high; while immunity rate measured by Anti-HBs was found to be low. Needle stick injury, contaminated sharp instruments injury andexposure to blood are the most significant occupational variables related to infection rate of HBV. Contaminated sharp instruments injury and exposure to blood, are the most significant occupational variables related to carrier rate. Date of needle stick injury, incidence and date of contaminated sharp instruments injury, incidence and date of exposure to blood have significant relation to immunity rate against HBV infection.Conclusion: The prevalence rate of HBV markers among HCWs in Public Teaching Hospitals in Khartoum State, Sudan, differs according to occupational hazard factors. With the exception of the HBeAg, seroprevalence of all HBV markers was found to be significantly correlated with occupational hazards (P<0.05).Key words: HBV markers, HCWs

Association between Knowledge and Drug Adherence in Patients with Hypertension in Quetta, Pakistan

Purpose: To evaluate the association between patient’s knowledge of hypertension management and medication adherence.Methods: A cross-sectional study was undertaken with 385 hypertensive patients who visited outpatient departments in two public hospitals in Quetta City, Pakistan. Besides demographic and disease-relatedquestions, two validated questionnaires (Hypertension Fact Questionnaire and Drug Attitude Inventory) were used for data collection. Descriptive statistics were to determine the demographic and diseasecharacteristics of the patients while Spearman rank correlation was employed to measure the association between knowledge and drug adherence.Results: Out of 385 patients, 236 (61.3 %) of the patients had average knowledge about hypertension while 249 (64.7 %) were categorized as poor adherent. No patient was considered as good adherent in the study. Correlation coefficient between total score of knowledge and total adherence was – 0.170 (p < 0.001), indicating an inverse association between knowledge scores and adherence level.Conclusion: Although the level of knowledge was average, patients were unsure of the benefits of continuous medication use which resulted in non-adherence to regimens. Educating patients about the benefits of medications and clarifying doubts regarding medication use should result in better control of hypertension

Community-based health insurance scheme in a rural community of North west Nigeria: a roadmap to achieving universal health coverage.

Community Based Health Insurance (CBHI) scheme is aimed at reducing out of pocket spending on health care services, ensuring final risk protection to all, especially the poor and the most vulnerable, improvement of quality of health care services, access and utilization as well as the promotion of equity. Objective: This research was aimed at determining willingness to participate in a community-based health insurance scheme among rural households in Katsina State. Method: A cross-sectional descriptive study was conducted in December 2016 among households of Batagarawa LGA, Katsina State. We used a pre-tested, electronic, semi-structured interviewer-administered questionnaire to obtain data from households that were selected using a multistage sampling technique and we analyzed the data using STATA version 13. Results: Most, (28.5%) of the respondents were in the age range of 30-39 years with a mean age of 35.5 years. Males were the dominant household heads (93%). Most were married (90%). Most, (90.5%) of households were willing to pay for a community-based health insurance scheme with a median premium of 100 Naira per household member per month. Conclusions: The high proportion of households willing to pay for the scheme should inform the decision of policy makers to design and maintain Community Based Health Insurance Scheme to improve access to and utilization of quality health care services

Determination of Gossypol in Hamid and Bt (Seeni 1) Cottonseed Oil using Fourier Transform Infrared Spectroscopy

This study was conducted to determine the gossypol content in Bt cottonseed (Seeni-1) oil by using Fourier Transform Infrared (FTIR) spectroscopy with an Attenuated Total Reflectance (ATR) element. The wavelengths used were selected by spiking refined, bleached deodorized palm oil (RBDPO) to gossypol concentrations of 0-5% and noting the regions of maximal absorbance. Absorbance values of the wavelength regions 3700-2400 &amp; 1900-750 cm−1 and a partial least squares (PLS) method were used to derive calibration models for Hamid cottonseed oil, Seeni-1 cottonseed oil, and gossypol-spiked RBDPO. The coefficients of determination (R2) for the calibration models were computed for the FTIR spectroscopy results against those found by using the wet chemical method AOCS method Ba 8–78. The R2 was 0.8916, 0.9581, and 0.9374 for Hamid cottonseed oil, Seeni-1 cottonseed oil, and gossypol-spiked RBDPO, respectively. The standard error (SE) of the calibration was 0.053, 0.078, and 0.062, respectively. The calibration models were validated using the cross-validation technique within the same set of oil samples. The results of FTIR spectroscopy as a useful technique determining gossypol content in crude cottonseed oil showed that there is a significant difference (p &lt;0.05) in the amount of gossypol content in Hamid and Bt Seeni-1 cottonseed oils

Peer review audit of trauma deaths in a developing country

OBJECTIVES: Peer review of trauma deaths can be used to evaluate the efficacy of trauma systems. The objective of this study was to estimate teh proportion of preventable trauma deaths and the factors contributing to poor outcome using peer review in a tertiary care hospital in a developing country. METHODS: All trauma deaths during a 2-year period (1 January 1998 to 30 December 1998) were identified and registered in a computerized trauma registry, and the probability of survival was calculated for all patients. Summary data, including registry information and details of prehospital, emergency room, and definitive care, were provided to all members of the peer review committee 1 week before the committee meeting. The committee then reviewed all cases and classified each death as preventable, potentially preventable, or non-preventable.RESULTS AND CONCLUSION: A total fo 279 patients were registered in the trauma registry during the study period, including 18 trauma deaths. Peer review judged that six were preventable, seven were potentially preventable, and four were non-preventable. One patient was excluded because the record was not available for review. The proportion of preventable and potentially preventable deaths was significantly higher in our study than from developed countries. Of the multiple contributing factors identified, the most important were inadequate prehospital transfer, limited hospital resources, and an absence of integrated and organized trauma care. This study summarizes the challenges faced in trauma care in a developing country

A comprehensive review on medical diagnosis using machine learning

The unavailability of sufficient information for proper diagnosis, incomplete or miscommunication between patient and the clinician, or among the healthcare professionals, delay or incorrect diagnosis, the fatigue of clinician, or even the high diagnostic complexity in limited time can lead to diagnostic errors. Diagnostic errors have adverse effects on the treatment of a patient. Unnecessary treatments increase the medical bills and deteriorate the health of a patient. Such diagnostic errors that harm the patient in various ways could be minimized using machine learning. Machine learning algorithms could be used to diagnose various diseases with high accuracy. The use of machine learning could assist the doctors in making decisions on time, and could also be used as a second opinion or supporting tool. This study aims to provide a comprehensive review of research articles published from the year 2015 to mid of the year 2020 that have used machine learning for diagnosis of various diseases. We present the various machine learning algorithms used over the years to diagnose various diseases. The results of this study show the distribution of machine learningmethods by medical disciplines. Based on our review, we present future research directions that could be used to conduct further research

Artificial neural network led optimization of oxyhydrogen hybridized diesel operated engine

The prevailing massive exploitation of conventional fuels has staked the energy accessibility to future generations. The gloomy peril of inflated demand and depleting fuel reservoirs in the energy sector has supposedly instigated the urgent need for reliable alternative fuels. These very issues have been addressed by introducing oxyhydrogen gas (HHO) in compression ignition (CI) engines in various flow rates with diesel for assessing brake-specific fuel consumption (BSFC) and brake thermal efficiency (BTE). The enrichment of neat diesel fuel with 10 dm3/min of HHO resulted in the most substantial decrease in BSFC and improved BTE at all test speeds in the range of 1000– 2200 rpm. Moreover, an Artificial Intelligence (AI) approach was employed for designing an ANN performance-predicting model with an engine operating on HHO. The correlation coefficients (R) of BSFC and BTE given by the ANN predicting model were 0.99764 and 0.99902, respectively. The mean root errors (MRE) of both parameters (BSFC and BTE) were within the range of 1%–3% while the root mean square errors (RMSE) were 0.0122 kg/kWh and 0.2768% for BSFC and BTE, respec-tively. In addition, ANN was coupled with the response surface methodology (RSM) technique for comprehending the individual impact of design parameters and their statistical interactions gov-erning the output parameters. The R2 values of RSM responses (BSFC and BTE) were near to 1 and MRE values were within the designated range. The comparative evaluation of ANN and RSM predicting models revealed that MRE and RMSE of RSM models are also well within the desired range but to be outrightly accurate and precise, the choice of ANN should be potentially endorsed. Thus, the combined use of ANN and RSM could be used effectively for reliable predictions and effective study of statistical interactions

A secure and lightweight drones-access protocol for smart city surveillance

The rising popularity of ICT and the Internet has enabled Unmanned Aerial Vehicle (UAV) to offer advantageous assistance to Vehicular Ad-hoc Network (VANET), realizing a relay node's role among the disconnected segments in the road. In this scenario, the communication is done between Vehicles to UAVs (V2U), subsequently transforming into a UAV-assisted VANET. UAV-assisted VANET allows users to access real-time data, especially the monitoring data in smart cities using current mobile networks. Nevertheless, due to the open nature of communication infrastructure, the high mobility of vehicles along with the security and privacy constraints are the significant concerns of UAV-assisted VANET. In these scenarios, Deep Learning Algorithms (DLA) could play an effective role in the security, privacy, and routing issues of UAV-assisted VANET. Keeping this in mind, we have devised a DLA-based key-exchange protocol for UAV-assisted VANET. The proposed protocol extends the scalability and uses secure bitwise XOR operations, one-way hash functions, including user's biometric verification when users and drones are mutually authenticated. The proposed protocol can resist many well-known security attacks and provides formal and informal security under the Random Oracle Model (ROM). The security comparison shows that the proposed protocol outperforms the security performance in terms of running time cost and communication cost and has effective security features compared to other related protocols