Good practice guide
Supporting community action on HIV, health and rights to end AIDS
Eur Respir J 2014; 43: 24–35 | DOI: 10.1183/09031936.00113413
PLoS ONE 7(12): e52986. doi:10.1371/journal.pone.0052986. Opern Access please download from the website
Bulletin of the World Health Organization, http://dx.doi.org/10.2471/BLT.16.178608
Original Research
African Journal of Primary Health Care & Family Medicine
ISSN: (Online) 2071-2936, (Print) 2071-2928
Open Access
DHS Working Papers No. 113
DHS Working Papers No. 110 | Zimbabwe Working Papers No. 11
Kan M et al. Journal of the International AIDS Society 2018, 21(S5):e25139 http://onlinelibrary.wiley.com/doi/10.1002/jia2.25139/full | https://doi.org/10.1002/jia2.25139
A review of current literature and up date data from the field, April 2015.
This report has been published in part in J Hosp Inf. 2015;90:1-9.
http://www.ncbi.nlm.nih.gov/pubmed/?term=ebola+nosocomial+shears
Ade et al. BMC Health Services Research (2016) 16:5
Background: In the “Centre National Hospitalier de Pneumo-Phtisiologie” of Cotonou, Benin, little is known about
the characteristics of patients who have not attended their scheduled appointment, the results of tracing and the
possible b...enefits on improving treatment outcomes. This study aimed to determine the contribution of tracing
activities for those who missed scheduled appointments towards a successful treatment outcome.
Methods: A retrospective cohort study was carried out among all smear-positive pulmonary tuberculosis patients
treated between January and September 2013. Data on demographic and diagnostic characteristics and treatment
outcomes were accessed from tuberculosis registers and treatment cards. Information on those who missed their
scheduled appointments was collected from the tracing tuberculosis register. A univariate analysis was performed
to explore factors associated with missing a scheduled appointment
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Topics in Antiviral Medicine 25 Issue 2 May/June 2017
PLoS ONE 13(8): e0202499. https://doi.org/10.1371/journal.pone.0202499
This was a school-based cross-sectional study conducted in 2015 among 305 school children aged 7–16 years from two primary schools located in Ilemela and Magu Districts, north-western Tanzania. Single stool and urine samples w...ere collected from each participant and examined for the presence of Schistosoma mansoni eggs, parasite antigen, and parasite DNA using KK thick smears, POC-CCA tests, and real-time PCR, respectively.
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DHS Further Analysis Reports No. 111
This study is a theory-driven analysis of the socio-demographic determinants of maternal care seeking in Kenya. Specifically, it examines predisposing, enabling, and need factors potentially associated with use of antenatal care (ANC), health facility delive...ry, and timely postnatal care (PNC).
This study uses data from the 2014 Kenya Demographic and Health Survey (KDHS) conducted among women age 15-49 with a live birth in the five years preceding the survey. It includes data from all 47 counties of Kenya, grouped contiguously into 12 regions. We apply Andersen’s Behavioral Model of Health Services Use to examine socio-demographic predictors of health service use. We estimate logistic regression models for adequate use of ANC (defined as attending at least four ANC visits, starting in the first three months of pregnancy), delivery in a health facility, and PNC within 48 hours of delivery.
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Levels and Inequities
DHS Further Analysis Reports No. 110
This study shows large variations in maternal health indicators across high-priority counties in Kenya. Nairobi exceeds the national average on all maternal health indicators in this study, while other highpriority counties consist...ently are disadvantaged compared with Kenya as a whole in most maternal health indicators. Kisumu exceeds the national average in use of antenatal care, delivery in a health facility, and postnatal care, but not other indicators. Nakuru has fewer women with fertility risk and fewer women who report that the distance they must travel to reach a health facility is a problem.
This study identifies a number of inequities in maternal health indicators across socio-demographic characteristics in the high-priority counties—most in the distribution of delivery care and least in antenatal care. Inequities are also observed in fertility risk and postnatal care.
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J Nepal Health Res Counc 2012 May;10(21):82-87
MICROBIAL DRUG RESISTANCEVolume 24, Number 5, 2018ªMary Ann Liebert, Inc.DOI: 10.1089/mdr.2017.0383
Antibiotic resistance (ABR) is a worldwide publichealth concern, with serious health, economic, and so-cietal repercussions. Its emergence is attributed to the se-lective pressure exerted by antib...iotic use in the community, hospitals, veterinary health, agriculture, aquaculture, and the environment. Additionally aggravating the situation is the fact that very few new antibiotics have recently been produced by pharmaceutical companies. It is widely acknowledged that food animals are key reservoirs of antibiotic-resistant bacteria and that antibiotic usage in this population favors the emergence, selection, and spread of resistance among animals and humans, both through zoonoses (infectious diseases trans-mitted between animals and humans) and the food chain.
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The Transatlantic Task Force on Antimicrobial Resistance (TATFAR) fosters cooperation between the European Union (EU) andthe United States (US) on the issue of antimicrobial resistance. The first TATFAR recommendation refers to appropriate use of antimicrobials in human medicine through hospital Ant...imicrobial Stewardship Programs (ASPs) and, specifically, to the development of common structure and process indicators of ASP. These indicators should allow characterization of programs and comparisons among healthcare systems in EU and US.
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This study is a theory-driven analysis of the socio-demographic determinants of maternal care seeking in Kenya. Specifically, it examines predisposing, enabling, and need factors potentially associated with use of antenatal care (ANC), health facility delivery, and timely postnatal care (PNC).This s...tudy uses data from the 2014 Kenya Demographic and Health Survey (KDHS) conducted among women age 15-49 with a live birth in the five years preceding the survey. It includes data from all 47 counties of Kenya, grouped contiguously into 12regions.We apply Andersen’s Behavioral Model of Health Services Use to examine socio-demographic predictors of health service use.We estimate logistic regression models for adequate use of ANC (defined as attending at least four ANC visits, starting in the first three months of pregnancy), delivery in a health facility, and PNC within 48 hours of delivery.
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Shortages of healthcare workers is detrimental to the health of communities, especially children. This paper describes the process of capacity building Community Health Volunteers (CHVs) to deliver integrated preventive and curative package of care of services to manage common childhood illness in h...ard-to-reach communities in Bondo Subcounty, Kenya
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