Willingness to Pay for Social Health Insurance Among Health Care Professionals in North Wollo Zone, Amhara Region, Ethiopia: Mixed Method Study

Background

Ethiopia introduced a social health insurance (SHI) scheme for the formal sector that will cost 3% of the monthly salary as a premium and provide universal health coverage. Since health care professionals (HCP) are the primary front-line service providers, their willingness to pay (WTP) for SHI may have a direct or indirect impact on how the programme is implemented. However, little is known about WTP for SHI among HCP.

Objective

To assess WTP for SHI and associated factors among government employee HCP in the North Wollo Zone, Northeast Ethiopia.

Methods

Using the contingent valuation method, a mixed approach and cross-sectional study design were applied. For the qualitative study design, in-depth interviews were performed with focal persons and officers of health insurance. Multistage systematic random sampling was used to select 636 healthcare professionals. Logistic regression analysis was used to determine independent predictors of WTP for SHI. Qualitative data were analyzed using thematic analysis.

Results

A response rate of 92.45% was achieved among the 636 participants, with 588 healthcare professionals completing the interview. The majority (61.7%) of participants were willing to join and pay the suggested SHI premium. Participants' WTP was significantly positively associated with the presence of under five years of children but their willingness to pay was significantly negatively associated with the female gender and increasing monthly salary. On the other hand, on the qualitative side, the amount of premium contribution, benefits package, and quality of service were the major factors affecting their WTP.

Conclusion

The majority of healthcare professionals were willing to pay for the SHI scheme, almost as much as the premium set by the government. This suggests proof that healthcare financing reform is feasible, particularly for the implementation of the SHI system.

Rapid detection of fast innovation under the pressure of COVID-19

Covid-19 has rapidly redefined the agenda of technological research and development both for academics and practitioners. If the medical scientific publication system has promptly reacted to this new situation, other domains, particularly in new technologies, struggle to map what is happening in their contexts. The pandemic has created the need for a rapid detection of technological convergence phenomena, but at the same time it has made clear that this task is impossible on the basis of traditional patent and publication indicators. This paper presents a novel methodology to perform a rapid detection of the fast technological convergence phenomenon that is occurring under the pressure of the Covid-19 pandemic. The fast detection has been performed thanks to the use of a novel source: the online blogging platform Medium. We demonstrate that the hybrid structure of this social journalism platform allows a rapid detection of innovation phenomena, unlike other traditional sources. The technological convergence phenomenon has been modelled through a network-based approach, analysing the differences of networks computed during two time periods (pre and post COVID-19). The results led us to discuss the repurposing of technologies regarding "Remote Control", "Remote Working", "Health" and "Remote Learning".

Quercetin potentializes the respective cytotoxic activity of gemcitabine or doxorubicin on 3D culture of AsPC-1 or HepG2 cells, through the inhibition of HIF-1α and MDR1

The impact of cancer on lifespan is significantly increasing worldwide. Enhanced activity of drug efflux pumps and the incidences of the tumor microenvironment such as the apparition of a hypoxic gradient inside of the bulk tumor, are the major causes of chemotherapy failure. For instance, expression of Hypoxia-inducible factor (HIF-1α) has been associated with metastasis, resistance to chemotherapy and reduced survival rate. One of the current challenges to fight against cancer is therefore to find new molecules with therapeutic potential that could overcome this chemoresistance. In the present study, we focused on the bioactive plant flavonoid quercetin, which has strong antioxidant and anti-proliferative properties. We examined the efficacy of combined treatments of quercetin and the anti-cancer drugs gemcitabine and doxorubicin, known to specifically act on human pancreatic and hepatic cancer cells, respectively. Moreover, our study aimed to investigate more in-depth the implication of the multidrug transporter MDR1 and HIF-1α n chemoresistance and if quercetin could act on the activity of the drug efflux pumps and the hypoxia-associated effects. We observed that the anti-cancer drugs, were more effective when administered in combination with quercetin, as shown by an increased percentage of dead cells up to 60% in both 2D and 3D cultures. In addition, our results indicated that the combination of anti-cancer drugs and quercetin down-regulated the expression of HIF-1α and increased the expression levels of the regulator of apoptosis p53. Moreover, we observed that quercetin could inhibit the efflux activity of MDR1. Finally, our in vitro study suggests that the efficiency of the chemotherapeutic activity of known anti-cancer drugs might be significantly increased upon combination with quercetin. This flavonoid may therefore be a promising pharmacological agent for novel combination therapy since it potentializes the cytotoxic activity of gemcitabine and doxorubicin on by targeting the chemoresistance developed by the pancreatic and liver cancer cells respectively.

Food hygiene practices and its associated factors among model and non model households in Abobo district, southwestern Ethiopia: Comparative cross-sectional study

BACKGROUND

In developing country most of human infectious diseases are caused by eating contaminated food. Estimated nine out ten of the diarrheal disease is attributable to the environment and associated with risk factors of poor food hygiene practice. Understanding the risk of eating unsafe food is the major concern to prevent and control food borne diseases. The main goal of this study was to assessing food hygiene practices and its associated factors among model and non model households at Abobo district.

METHODS

This study was conducted from 18 October 2013 to 13 June 2014. A community-based comparative cross-sectional study design was used. Pretested structured questionnaire was used to collect data. A total of 1247 households (417 model and 830 non model households) were included in the study from Abobo district. Bivariate and multivariate logistic regression analysis was used to identify factors associated with outcome variable.

RESULTS

The study revealed that good food hygiene practice was 51%, of which 79% were model and 36.70% were non model households. Type of household [AOR: 2.07, 95% CI: (1.32-3.39)], sex of household head [AOR: 1.63, 95% CI: (1.06-2.48)], Availability of liquid wastes disposal pit [AOR: 2.23, 95% CI: (1.39,3.63)], Knowledge of liquid waste to cause diseases [AOR: 1.95, 95% (1.23,3.08)], and availability of functional hand washing facility [AOR: 3.61, 95% CI: (1.86-7.02)] were the factors associated with food handling practices.

CONCLUSION

This study revealed that good food handling practice is low among model and non model households. While type of household (model versus non model households), sex, knowledge of solid waste to cause diseases, availability of functional hand washing facility, and availability of liquid wastes disposal pit were the factors associated with outcome variable. Health extension workers should play a great role in educating households regarding food hygiene practices to improve their knowledge and practices of the food hygiene.

Least mean square fourth based microgrid state estimation algorithm using the internet of things technology

This paper proposes an innovative internet of things (IoT) based communication framework for monitoring microgrid under the condition of packet dropouts in measurements. First of all, the microgrid incorporating the renewable distributed energy resources is represented by a state-space model. The IoT embedded wireless sensor network is adopted to sense the system states. Afterwards, the information is transmitted to the energy management system using the communication network. Finally, the least mean square fourth algorithm is explored for estimating the system states. The effectiveness of the developed approach is verified through numerical simulations.