Feasibility of visualizing cancer incidence data at sub-county level: Findings from 21 National Program of Cancer Registries.

Monitoring cancer incidence data by geography is useful for planning public health activities. However, due to anticipated confidentiality and statistical reliability issues, data on cancer incidence and mortality are more often displayed at a national, state, or county level, rather than at more local levels. To address this gap in displaying cancer data at the local level, the CDC's National Environmental Public Health Tracking Program and 21 National Program of Cancer Registries worked together on a pilot project to examine the feasibility of displaying sub-county-level incidence of selected cancer types diagnosed during 2007-2016. The results from this project are important steps for building sub-county cancer displays into data visualizations and using the data in a way that provides meaningful insights. The availability of sub-county cancer data may allow researchers to better examine cancer data at a local level which may help guide public health decisions regarding community-based interventions and screening services.

Challenges influencing proper implementation of quality health care referral system in Kaloleni Sub-county, Kilifi County in Kenya.

The reason behind having referral system in Kenya is to have proper distribution of effective health care services to all Kenyans as well as linking and integrating medical services across all levels of healthcare. In Kenya, most of levels of health care lacks specialized manpower and equipment, proper communication strategies, knowledge on referral system and skilled health workers to deal with referral system. Therefore, this study addresses the challenges influencing the proper implementation of quality referral system of health care in Kaloleni sub-county, Kilifi County in Kenya. Specifically, investigating gaps by the health workers, knowledge and communication factors on implementation of quality health care referral system. A cross-sectional research design was used targeting health care workers in public health care facilities. Self- administered questionnaires were used to obtain quantitative data. The data was cleaned, coded and analyzed using SPSS V. 22. The inferential statistics discussed finding from Chi-square showing the significance between independent and dependent variables. According to the results, Communication gap with p(0.18) showed to have more significant variable affecting the quality referral system followed by knowledge factor with significant of p(0.499) and finally Nurse's skills with significant ofp(0.99).

Mapping of anaemia prevalence among pregnant women in Kenya (2016-2019).

BACKGROUND: Reducing the burden of anaemia is a critical global health priority that could improve maternal outcomes amongst pregnant women and their neonates. As more counties in Kenya commit to universal health coverage, there is a growing need for optimal allocation of the limited resources to sustain the gains achieved with the devolution of healthcare services. This study aimed to describe the spatio-temporal patterns of maternal anaemia prevalence in Kenya from 2016 to 2019. METHODS: Quarterly reported sub-county level maternal anaemia cases from January 2016 - December 2019 were obtained from the Kenyan District Health Information System. A Bayesian hierarchical negative binomial spatio-temporal conditional autoregressive (CAR) model was used to estimate maternal anaemia prevalence by sub-county and quarter. Spatial and temporal correlations were considered by assuming a conditional autoregressive and a first-order autoregressive process on sub-county and seasonal specific random effects, respectively. RESULTS: The overall estimated number of pregnant women with anaemia increased by 90.1% (95% uncertainty interval [95% UI], 89.9-90.2) from 155,539 cases in 2016 to 295,642 cases 2019. Based on the WHO classification criteria, the proportion of sub-counties with normal prevalence decreased from 28.0% (95% UI, 25.4-30.7) in 2016 to 5.4% (95% UI, 4.1-6.7) in 2019, whereas moderate anaemia prevalence increased from 16.8% (95% UI, 14.7-19.1) in 2016 to 30.1% (95% UI, 27.5-32.8) in 2019 and severe anaemia prevalence increased from 7.0% (95% UI, 5.6-8.6) in 2016 to 16.6% (95% UI, 14.5-18.9) in 2019. Overall, 45.1% (95% UI: 45.0-45.2) of the estimated cases were in malaria-endemic sub-counties, with the coastal endemic zone having the highest proportion 72.8% (95% UI: 68.3-77.4) of sub-counties with severe prevalence. CONCLUSION: As the number of women of reproductive age continues to grow in Kenya, the use of routinely collected data for accurate mapping of poor maternal outcomes remains an integral component of a functional maternal health strategy. By unmasking the sub-county disparities often concealed by national and county estimates, our study findings reiterate the importance of maternal anaemia prevalence as a metric for estimating malaria burden and offers compelling policy implications for achieving national nutritional targets.

Developing a surveillance system of sub-county data: Finding suitable population thresholds for geographic aggregations.

The Centers for Disease Control and Prevention's National Environmental Public Health Tracking Program created standardized sub-county geographies that are comparable over time, place, and outcomes. Expected census tract-level counts were calculated for asthma emergency department visits and lung cancer. Census tracts were aggregated for various total population and sub-population thresholds, then suppression and stability were examined. A total of 5,000 persons was recommended for the more common outcome scheme and a total of 20,000 persons was recommended for the rare outcome scheme. Health outcomes with a median case count of 17.0 cases or higher should produce stable estimates at the census tract level. This project generated recommendations for three sub-county geographies that will be useful for surveillance purposes: census tract, a more common outcome aggregation scheme, and a rare outcome aggregation scheme. This methodology can be applied anywhere to aggregate geographic units and produce stable rates at a finer resolution.

The differential effect of the free maternity services policy in Kenya.

BACKGROUND: The Government of Kenya introduced the free maternity services (FMS) policy to enable mothers deliver at a health facility and thus improve maternal health indicators. AIM: The aim of this study was to determine if there was a differential effect of the policy by region (sub-county) and by facility type (hospitals vs. primary healthcare facilities [PHCFs]). SETTING: The study was conducted in Nyamira County in western Kenya. METHODS: This was an interrupted time series study where 42 data sets (24 pre- and 18 post-intervention) were collected for each observation. Monthly data were abstracted from the District Health Information System-2, verified, keyed into and analysed by using IBM-Statistical Package for the Social Sciences (SPSS-17). RESULTS: The relative effect of the policy on facility deliveries in the county was an increase of 22.5%, significant up to the 12th month (p < 0.05). The effect of the policy on deliveries by region was highest in Nyamira North and Masaba North (p < 0.001 up to the 18th month). The effect was larger (46.5% vs. 18.3%) and lasted longer (18 months vs. 6 months) in the hospitals than in the PHCFs. The increase in hospital deliveries was most significant in Nyamira North (61%; p < 0.001). There was a medium-term effect on hospital deliveries in Borabu (up to 9 months) and an effect that started in the sixth month in Manga. The relative effect of the policy on facility deliveries in PHCFs was only significant in Nyamira North and Masaba North (p < 0.001). CONCLUSION: The effect of the FMS policy was varied by region (sub-county) and by facility type.

Micro-planning in a wide age range measles rubella (MR) campaign using mobile phone app, a case of Kenya, 2016.

INTRODUCTION: A Measles rubella campaign that targeted 9 months to 14 year old children was conducted in all the 47 counties in Kenya between 16th and 24th of May 2016. Micro-planning using an android phone-based app was undertaken to map out the target population and logistics in all the counties 4 weeks to the campaign implementation instead of 6 months as per the WHO recommendation. The outcomes of the micro-planning exercise were a detailed micro-plan that served as a guide in ensuring that every eligible individual in the population was vaccinated with potent vaccine. A national Trainer of Trainers training was done to equip key officers with new knowledge and skills in developing micro-plans at all levels. The micro planning was done using a mobile phone app, the doforms that enabled data to be transmitted real time to the national level. The objective of the study was to establish whether use of mobile phone app would contribute to quality of sub national micro plans that can be used for national level planning and implementation of the campaign. METHODS: There were 9 data collection forms but only forms 1-7 were to be uploaded onto the app. Forms 8A and 9A were to be filled but were to remain at the implementation level for use intra campaign. The forms were coded; Form 1A&B, 2A, 3A, 4A, 5A, 6A, 7A, 8A and 9A The Village form (form 1A&B) captured information by household which included village names, name of head of household, cell phone contact of head of household, number of children aged 9 months to 14years in the household, possible barriers to reaching the children, appropriate vaccination strategy based on barriers identified and estimated or proposed number of teams and type. This was the main form and from this every other form picked the population figures to estimate other supplies and logistics. On advocacy, communication and social mobilization the information collected included mobile network coverage, public amenities such as churches, mosques and key partners at the local level. On human resource and cold chain supplies the information collected included number of health facilities by type, number of health workers by cadre in facilities within the village, number of vaccine carriers and icepacks by size, refrigerators and freezers. All these forms were to be uploaded onto the phone app. except form 8A, the individual team plan, which was to be used during implementation at the local level. Android phone application, doforms, was used to capture data. Training on micro planning, data entry and doforms app was conducted at National, County, Sub-county and ward levels using standardized guidelines. An interactive case study was used in all the trainings to facilitate understanding. The App was also available on Laptops through its provided web-application. The app allowed multiple users to log in concurrently. Feedback on all the variables were obtained from the team at the Ward level. The ward level team included education officers or teachers, village elders, community health workers and other community stakeholders. Only the Ward level was allowed to collect information on paper and that information was subsequently transferred to the phone-based app, doforms, by health information officers. The national, county and sub county were able to access their data from the app using a password provided by the administrator. RESULTS: Real time data was received from 46 of 47 counties. One county (Marsabit) did not participate in the micro plan process. Over 97% (283/290) of the sub counties responded and shared various information via the app. Different data forms had different completion rates. There was 100% completion rate for the data on villages and target population. Much valuable information was shared but there was no time for the national and county level to interrogate and harmonize for proper implementation. The information captured during the campaign can be used for routine immunization and other community based interventions. Electronic data collection not only provided the number of children but provided the locations also where these children could be found. CONCLUSION: Despite the limitations of time to harmonize the micro plans with the national plan, the micro planning process was a great success with 46/47 counties responding through the mobile phone app. Not only did it provide the numbers of the target children, it further provided the places where these children could be found. There was timely data transfer, data integrity, tracking, real time data visualization reporting and analysis. The app enabled real time feedback to national focal point by data entry clerks as well as enabling trouble shooting by the administrator. This ensured campaign planning was done from the lowest level to the national level.

Ethnobotanical survey of traditionally used medicinal plants for infections of skin, gastrointestinal tract, urinary tract and the oral cavity in Borabu sub-county, Nyamira county, Kenya.

ETHNOPHARMACOLOGICAL RELEVANCE: Different communities throughout the world have specialized and profound knowledge on the use medicinal plants for various diseases. However, the detailed information on the respective use may extinct in near future as this knowledge is passed only orally among generations in most of the communities. AIM OF THE STUDY: The present survey aimed to document the use of medicinal plants by traditional healers from the Kisii community, Borabu sub-county in Nyamira county, Kenya, to treat infections of the urinary tract, oral cavity, gastrointestinal system and the skin and to evaluate the social context in which the healers work and practice. MATERIALS AND METHODS: Validated questionnaires were applied to 50 traditional healers in the study region, followed by interviews and structured conversations. Information on the relevant traditionally used medicinal plants and their use were documented, including sampling and identification of voucher specimens. RESULTS: The ethnopharmacological survey revealed 25 medicinal plant species belonging to 19 families. It got evident that most of these species will be extinct in the near future unless appropriate measures are taken, as it turned out difficult to collect some of the wild growing species. Elaeodendron buchananii Loes, Erlangea marginata S. Moore, Acacia gerrardii Benth., Balanites orbicularis Sprague, Solanum renschii Vatke and Orthosiphon hildebrandtii Vatke have not been described before for its medicinal use. Among the 25 species collected from the various regions of Borabu sub-county Urtica dioica L. was the only medicinal plant that was collected from all regions. In contrast Erythrina abyssinica and Rhus natalensis were found in only two regions of the study area. CONCLUSION: The traditional medicinal use of the reported plants for infections should be documented and a great need of awareness from scientists and local government for improved preservation or field cultivation of some species is obvious.