Background Mobile technologies to improve blood pressure control in resource-limited settings are needed. We adapted and evaluated the acceptability and feasibility of PositiveLinks, a mobile phone application for self-monitoring, social support, and engagement in care for people living with HIV, among patients with hypertension in rural Uganda. Methods We enrolled adults on treatment for hypertension at Mbarara Regional Referral Hospital and Mbarara Municipal health center IV, southwestern Uganda. We provided and educated all participants on the use of PositiveLinks application and automated blood pressure monitors. We administered a baseline questionnaire and performed in-depth interviews 30 days later to explore acceptability, feasibility, medication adherence, social support, and blood pressure control. Results A total of 37 participants completed the interviews, mean age of 58 years (SD 10.8) and 28 (75.7%) were female. All participants embraced the PositiveLinks mobile app and were enthusiastic about self-monitoring of blood pressure, 35 (94.6%) experienced peer to peer support. Among the 35 participants non-adherent to medications at baseline, 31 had improved medication adherence. All except 1 of the 31(83.8%) who had uncontrolled blood pressure at baseline, had self-reported controlled blood pressure after 30 days of use of PositiveLinks. Conclusion Patients with hypertension in rural Uganda embraced the PositiveLinks mobile application and had improved medication adherence, social support, and blood pressure control. Further assessment of cost-effectiveness of the application in blood pressure control in resource-limited settings will be pursued in future studies.

Solid waste management has continued to be an increasing challenge worldwide and the situation has become worse in urban areas of developing countries. The rapid urban population growth, mainly due to high immigration and birth rates, has led to large amounts of solid waste, making it difficult for authorities to effectively manage the accumulated waste. Existing mathematical models of solid waste accumulation consider solid waste management by an external effort and do not address the contribution of the population in the management process. In this study, a mathematical model of solid waste accumulation is developed and analysed incorporating parameters for human immigration and solid waste recycling by particular population age groups. The solid waste is considered to be of two categories: biodegradable and non-biodegradable. Existence of equilibrium points is established and their stability analysed. Numerical simulations are done using MATLAB and Maple. Results show that solid waste increases with increasing human population and thus a solid waste free environment cannot be achieved. Sensitivity analysis suggests that improving the biodegradability of solid waste coupled with aiding solid waste decay and recycling reduces the final size of solid waste.

Purpose: The main purpose of this study was to examine the application of sensors and sensor networks for detection of people crowds in developing cities. This paper discusses unique challenges associated with people crowd detection especially in the urban towns of developing countries and gives a comparative review and analysis of popular human sensing approaches in the detection of people crowds. Methodology: This study provides a survey and categorization of popular human sensing approaches using literature especially published within the past two decades. The paper then analyzes current human sensing technologies vis-à-vis people crowd detection in developing cities. The respective strengths and shortfalls of various approaches are highlighted. Finally, by means of examples, a comparative analysis of different human sensing categories is carried out. Findings: The spontaneous, dynamic and chaotic nature of people crowds, together with the poor infrastructural development characteristic of developing economies pose unique challenges to the effectiveness of people crowd detection systems. Although there are advances in crowd detection, most of these are in the area of non-people crowds, while most of the research done on people crowd detection have been on indoor crowd settings. In addition, challenges unique to people crowd detection in developing countries include: scalability and cost of crowd detection systems, security of the detection system infrastructure, confidentiality of subjects being monitored, requirements for incentives and the ability to support passive and real time people crowd detection. Unique contribution to theory, practice and policy: This study emphasizes the need for both indoor and outdoor people crowd detection systems appropriate for the needs of developing cities. The study contributes to the body of knowledge since people crowds unlike other types of crowds present a unique set of challenges that call for special attention.

Objective: The objective of this study was to examine and propose the use of wireless sensor networks for people crowd detection in resource constrained environments such as developing economies. Methodology: A systematic review was carried out on current technological trends and application of Wireless Sensor Networks (WSNs) in crowd detection.  For this study, focus was on WSN implementation in developing economies, where infrastructure is underdeveloped and people crowds are dynamic and spontaneous. Based on a requirement analysis and knowledge of the inherent challenges of WSNs, a WSN implementation for people crowd detection was proposed. Findings: Most studies in crowd detection using WSNs, have been in the area of non-people crowds. However issues critical to deployment of WSNs for people crowd detection in developing countries include: the uncontrollable nature of people crowds, under developed physical infrastructure and the inherent challenges of power, computational capacity and broadcast communication characterizing WSNs. Achieving people crowd detection using WSNs therefore, calls for special attention. Recommendation: To ensure effective people crowd detection, requires taking into consideration connectivity, scalability, performance, security, accuracy and resource utilization of WSNs.