13 research outputs found

    Adherence to Cancer Prevention Guidelines in 18 African Countries

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    Background Cancer rates in Africa are projected to double by 2030 due to aging and increased exposure to cancer risk factors, including modifiable risk factors. We assessed adherence to 5 modifiable cancer risk factors across 18 African countries. Methods Data on adults 18 years and older were obtained from the 2002–2004 World Health Survey. Adherence to current World Cancer Research Fund guidelines on smoking, alcohol, body weight, physical activity, and nutrition was assessed. Adherence scores ranged from 0 (no guideline met) to 5 (all guidelines met). Determinants of adherence were assessed using multivariable linear regression adjusted for individual and country level characteristics. Results Across all countries, adherence to the guidelines among adults was high for smoking (72%–99%) and alcohol (85%–100%), but low for body weight (1.8%–78%), physical activity (3.4%–84%) and nutrition (1.4%–61%). Overall adherence score ranged from 2.32 in Mali to 3.72 in Comoros. In multivariable models, residing in low versus high SES households was associated with reduced adherence by 0.24 and 0.21 points for men and women respectively after adjusting for age, gender, education, and marital status (p<0.001). Every % increase in GDP spent on health was associated with increased adherence by 0.03 in men and 0.09 in women (p<0.001). Conclusions The wide variation in adherence to cancer prevention guidelines observed across countries and between population sub-groups suggests the need for targeted public health efforts to improve behaviors related to body weight, physical activity and nutrition

    Cost of wastewater-based environmental surveillance for SARS-CoV-2: evidence from pilot sites in Blantyre, Malawi and Kathmandu, Nepal

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    Environmental surveillance of rivers and wastewater for SARS-CoV-2 detection has been explored as an innovative way to surveil the pandemic. This study estimated the economic costs of conducting wastewater-based environmental surveillance for SARS-CoV-2 to inform decision making if countries consider continuing these efforts. We estimated the cost of two SARS-CoV-2 environmental surveillance pilot studies conducted in Blantyre, Malawi, and Kathmandu, Nepal. The cost estimation accounted for the consumables, equipment, and human resource time costs used for environmental surveillance from sample selection until pathogen detection and overhead costs for the projects. Costs are reported in 2021 USandreportedascostspermonth,persampleandpersonperyear.Theestimatedcostsforenvironmentalsurveillancerangefrom and reported as costs per month, per sample and person per year. The estimated costs for environmental surveillance range from 6,175 to 8,272permonth(Blantyresite)and8,272 per month (Blantyre site) and 16,756 to 30,050(Kathmandusite).Thenumberofsamplesprocessedpermonthrangedfrom84to336attheBlantyresiteand96to250attheKathmandusite.ConsumablescostsarevariablecostsinfluencedbythenumberofsamplesprocessedandarealargeshareofthemonthlycostsforES(rangingfrom3930,050 (Kathmandu site). The number of samples processed per month ranged from 84 to 336 at the Blantyre site and 96 to 250 at the Kathmandu site. Consumables costs are variable costs influenced by the number of samples processed and are a large share of the monthly costs for ES (ranging from 39% to 72%). The relatively higher costs per month for the Kathmandu site were attributable to the higher allocation of dedicated human resources and equipment to environmental surveillance for SARS-CoV-2 compared to the Blantyre site where these resources were shared with other activities. The average cost per sample ranged from 25 to 74(Blantyre)and74 (Blantyre) and 120 to 175(Kathmandu).Therewereassociatedeconomiesofscaleforhumanresourcesandequipmentcostswithincreasedsampleprocessingandsharingofresourceswithotheractivities.Thecostperpersoninthecatchmentareaperyearrangedfrom175 (Kathmandu). There were associated economies of scale for human resources and equipment costs with increased sample processing and sharing of resources with other activities. The cost per person in the catchment area per year ranged from 0.07 to 0.10inBlantyreand0.10 in Blantyre and 0.07 to $0.13 in Kathmandu. Environmental surveillance may be a low-cost early warning signal for SARS-CoV-2 that can complement other SARS-CoV2 monitoring efforts

    Health care access dimensions and cervical cancer screening in South Africa: analysis of the world health survey.

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    Background Cervical cancer is the most commonly diagnosed cancer and the leading cause of cancer mortality among women in sub-Saharan Africa. Recent recommendations for cervical cancer primary prevention highlight HPV vaccination, and secondary prevention through screening. However, few studies have examined the different dimensions of health care access, and how these may influence screening behavior, especially in the context of clinical preventive services. Methods Using the 2003 South Africa World Health Survey, we determined the prevalence of cervical cancer screening with pelvic examinations and/or pap smears among women ages 18 years and older. We also examined the association between multiple dimensions of health care access and screening focusing on the affordability, availability, accessibility, accommodation and acceptability components. Results About 1 in 4 (25.3%, n = 65) of the women who attended a health care facility in the past year got screened for cervical cancer. Screened women had a significantly higher number of health care providers available compared with unscreened women (mean 125 vs.12, p-value Conclusions Our findings suggest that cost issues (affordability component) and other patient level factors (captured in the acceptability, accessibility and accommodation components) were less important predictors of screening compared with availability of physicians in this population. Meeting cervical cancer screening and HPV vaccination goals will require significant investments in the health care workforce, improving health care worker density in poor and rural areas, and improved training of the existing workforce

    Perspectives on the use of modelling and economic analysis to guide HIV programmes in sub-Saharan Africa

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    HIV modelling and economic analyses have had a prominent role in guiding programmatic responses to HIV in sub-Saharan Africa. However, there has been little reflection on how the HIV modelling field might develop in future. HIV modelling should more routinely align with national government and ministry of health priorities, recognising their legitimate mandates and stewardship responsibilities, for HIV and other wider health programmes. Importance should also be placed on ensuring collaboration between modellers, and that joint approaches to addressing modelling questions, becomes the norm rather than the exception. Such an environment can accelerate translation of modelling analyses into policy formulation because areas where models agree can be prioritised for action, whereas areas over which uncertainty prevails can be slated for additional study, data collection, and analysis. HIV modelling should increasingly be integrated with the modelling of health needs beyond HIV, particularly in allocative efficiency analyses, where focusing on one disease over another might lead to worse health overall. Such integration might also enhance partnership with national governments whose mandates extend beyond HIV. Finally, we see a need for there to be substantial and equitable investment in capacity strengthening within African countries, so that African researchers will increasingly be leading modelling exercises. Building a critical mass of expertise, strengthened through external collaboration and knowledge exchange, should be the ultimate goal

    Perspectives on the use of modelling and economic analysis to guide HIV programmes in sub-Saharan Africa

    Get PDF
    HIV modelling and economic analyses have had a prominent role in guiding programmatic responses to HIV in sub-Saharan Africa. However, there has been little reflection on how the HIV modelling field might develop in future. HIV modelling should more routinely align with national government and ministry of health priorities, recognising their legitimate mandates and stewardship responsibilities, for HIV and other wider health programmes. Importance should also be placed on ensuring collaboration between modellers, and that joint approaches to addressing modelling questions, becomes the norm rather than the exception. Such an environment can accelerate translation of modelling analyses into policy formulation because areas where models agree can be prioritised for action, whereas areas over which uncertainty prevails can be slated for additional study, data collection, and analysis. HIV modelling should increasingly be integrated with the modelling of health needs beyond HIV, particularly in allocative efficiency analyses, where focusing on one disease over another might lead to worse health overall. Such integration might also enhance partnership with national governments whose mandates extend beyond HIV. Finally, we see a need for there to be substantial and equitable investment in capacity strengthening within African countries, so that African researchers will increasingly be leading modelling exercises. Building a critical mass of expertise, strengthened through external collaboration and knowledge exchange, should be the ultimate goal
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