BackgroundEstimately, 70–80% of cancer cases are diagnosed in late stages in Kenya with breast cancer being a common cause of mortality among women where late diagnosis is the major ubiquitous concern. Numerous studies have focused on epidemiological and health policy dynamics essentially underestimating the determining factors that shape people’s choices and cues to health care service uptake. The study sought to evaluate the knowledge, attitude and health seeking behavior towards breast cancer and its screening in a quest to explain why women present for prognosis and treatment when symptomatic pointers are in advanced stages, impeding primary prevention strategies.MethodsEight focus groups (6–10 members per group) and four key informant interviews were conducted among adult participants from rural and urban settings. Sessions were audio-recorded and transcribed. A thematic analysis of the data was based on the concepts of the health belief model. Data analysis was conducted using NVIVO10.ResultsMost women perceived breast cancer as a fatal disease and conveyed fear of having early screening. Rural women preferred self-prescribed medications and the use of alternative medicine for long periods before presenting for professional care on suspicion that the lump is cancerous. Accessibility to equipped health facilities, lack of information to establish effective follow-up treatment and low-income status were underscored as their major health seeking behavior barriers whereas, urban women identified marital status as their main barrier. Key informant interviews revealed that health communication programs emphasized more on communicable diseases. This could in part explain why there is a high rate of misconception and suspicion about breast cancer among rural and urban women in the study setting.ConclusionsCreating breast cancer awareness alongside clear guidelines on accessing screening and treatment infrastructure is critical. It was evident, a diagnosis of breast cancer or lump brings unexpected confrontation with mortality; fear, pain, cultural barriers, emotional and financial distress. Without clear referral channels to enable those with suspicious lumps or early stage disease to get prompt diagnosis and treatment, then well-meaning awareness will not necessarily contribute to reducing morbidity and mortality.Electronic supplementary materialThe online version of this article (10.1186/s12905-018-0571-7) contains supplementary material, which is available to authorized users.

This study investigated the effectiveness of Water Safety Plans (WSP) implemented in 99 water supply systems across 12 countries in the Asia-Pacific region. An impact assessment methodology including 36 indicators was developed based on a conceptual framework proposed by the Center for Disease Control (CDC) and before/after data were collected between November 2014 and June 2016. WSPs were associated with infrastructure improvements at the vast majority (82) of participating sites and to increased financial support at 37 sites. In addition, significant changes were observed in operations and management practices, number of water safety-related meetings, unaccounted-for water, water quality testing activities, and monitoring of consumer satisfaction. However, the study also revealed challenges in the implementation of WSPs, including financial constraints and insufficient capacity. Finally, this study provided an opportunity to test the impact assessment methodology itself, and a series of recommendations are made to improve the approach (indicators, study design, data collection methods) for evaluating WSPs.

Microbial water quality monitoring is crucial for managing water resources and protecting public health. However, institutional testing activities in sub-Saharan Africa are currently limited. Because the economics of water quality testing are poorly understood, the extent to which cost may be a barrier to monitoring in different settings is unclear. This study used cost data from 18 African monitoring institutions (piped water suppliers and health surveillance agencies in six countries) and estimates of water supply type coverage from 15 countries to assess the annual financial requirements for microbial water testing at both national and regional levels, using World Health Organization recommendations for sampling frequency. We found that a microbial water quality test costs 21.0 ± 11.3 USD, on average, including consumables, equipment, labor, and logistics, which is higher than previously calculated. Our annual cost estimates for microbial monitoring of piped supplies and improved point sources ranged between 8 000 USD for Equatorial Guinea and 1.9 million USD for Ethiopia, depending primarily on the population served but also on the distribution of piped water system sizes. A comparison with current national water and sanitation budgets showed that the cost of implementing prescribed testing levels represents a relatively modest proportion of existing budgets (<2%). At the regional level, we estimated that monitoring the microbial quality of all improved water sources in sub-Saharan Africa would cost 16.0 million USD per year, which is minimal in comparison to the projected annual capital costs of achieving Sustainable Development Goal 6.1 of safe water for all (14.8 billion USD).

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BackgroundWater quality testing is critical for guiding water safety management and ensuring public health. In many settings, however, water suppliers and surveillance agencies do not meet regulatory requirements for testing frequencies. This study examines the conditions that promote successful water quality monitoring in Africa, with the goal of providing evidence for strengthening regulated water quality testing programs.Methods and findingsWe compared monitoring programs among 26 regulated water suppliers and surveillance agencies across six African countries. These institutions submitted monthly water quality testing results over 18 months. We also collected qualitative data on the conditions that influenced testing performance via approximately 821 h of semi-structured interviews and observations. Based on our qualitative data, we developed the Water Capacity Rating Diagnostic (WaterCaRD) to establish a scoring framework for evaluating the effects of the following conditions on testing performance: accountability, staffing, program structure, finances, and equipment & services. We summarized the qualitative data into case studies for each of the 26 institutions and then used the case studies to score the institutions against the conditions captured in WaterCaRD. Subsequently, we applied fuzzy-set Qualitative Comparative Analysis (fsQCA) to compare these scores against performance outcomes for water quality testing. We defined the performance outcomes as the proportion of testing Targets Achieved (outcome 1) and Testing Consistency (outcome 2) based on the monthly number of microbial water quality tests conducted by each institution. Our analysis identified motivation & leadership, knowledge, staff retention, and transport as institutional conditions that were necessary for achieving monitoring targets. In addition, equipment, procurement, infrastructure, and enforcement contributed to the pathways that resulted in strong monitoring performance.ConclusionsOur identification of institutional commitment, comprising motivation & leadership, knowledge, and staff retention, as a key driver of monitoring performance was not surprising: in weak regulatory environments, individuals and their motivations take-on greater importance in determining institutional and programmatic outcomes. Nevertheless, efforts to build data collection capacity in low-resource settings largely focus on supply-side interventions: the provision of infrastructure, equipment, and training sessions. Our results indicate that these interventions will continue to have limited long-term impacts and sustainability without complementary strategies for motivating or incentivizing water supply and surveillance agency managers to achieve testing goals. More broadly, our research demonstrates both an experimental approach for diagnosing the systems that underlie service provision and an analytical strategy for identifying appropriate interventions.