Capacity Building in Geoprocessing

Manual used for the implementation of CDE's Geoprocessing courses in the South and East. Composed of 6 modules covering important aspects of GIS handling and implementation: 1) Introduction to GIS; 2) Management issues; 3) GIS data preparation; 4) GIS data presentation; 5) Vector data analysis; 6) Raster data analysis. At the moment the manual is designed for use with ArcGIS. Work on a manual for use with open source software is currently ongoing. This manual was successfully used during several GIS training events in Kenya and Tajikistan.

Upper Ewaso Ngiro River Basin Water Management Information Platform: Survey on Development priorities, Information Needs and Conflict Management Efforts

A survey of development priorities and needs for water related information, including information on Water User Associations

Ewaso Ngiro and Meru Ecosystems Elephant Corridors: Site 1-6

7 maps illustrating the elephant corridors in different sites of Ewaso Ngiro, Kenya.

EIRS: Ewaso Incident Reporting System

Ewaso Incident Reporting System: reports on human-elephant interaction in Laikipia

Cognitive Cities: An Application for Nairobi. Text Message Participation of Slum Inhabitants to Improve Sanitary Facilities

Population growth is always increasing, and thus the concept of smart and cognitive cities is becoming more important. Developed countries are aware of and working towards needed changes in city management. However, emerging countries require the optimization of their own city management. This chapter illustrates, based on a use case, how a city in an emerging country can quickly progress using the concept of smart and cognitive cities. Nairobi, the capital of Kenya, is chosen for the test case. More than half of the population of Nairobi lives in slums with poor sanitation, and many slum inhabitants often share a single toilet, so the proper functioning and reliable maintenance of toilets are crucial. For this purpose, an approach for processing text messages based on cognitive computing (using soft computing methods) is introduced. Slum inhabitants can inform the responsible center via text messages in cases when toilets are not functioning properly. Through cognitive computer systems, the responsible center can fix the problem in a quick and efficient way by sending repair workers to the area. Focusing on the slum of Kibera, an easy-to-handle approach for slum inhabitants is presented, which can make the city more efficient, sustainable and resilient (i.e., cognitive).

The use of special stains at two dermatopathology laboratories in East Africa.

BACKGROUND Histopathology is often essential to establish an accurate diagnosis. Pathology laboratories are scarce in most Sub-Saharan Africa where dermatopathology is a developing field. In resource-poor countries, most specimens are analyzed only after hematoxylin and eosin staining. The availability of special stains is very limited and restricted to only few centers. The aim of this study is to analyze the extent of dermatopathological cases which can be adequately diagnosed after hematoxylin and eosin alone. Secondly, to investigate which cases required further special stains. METHODS All skin specimens submitted to two University Hospitals (Tanzania and Kenya) were included in this study. All specimens were first analyzed with hematoxylin and eosin and a diagnosis established when possible. All cases in which an accurate diagnosis after hematoxylin and eosin only was not possible, were registered and evaluated after further special stains. RESULTS A total of 386 specimens were examined. A proper histopathologic diagnosis with hematoxylin and eosin alone was possible in 344 (89.1%) samples. In 45 (11.6%) cases, mostly skin infections, further special stains were necessary. CONCLUSION A proper histopathologic diagnosis was possible after hematoxylin and eosin alone in almost 90% of the specimens submitted to the two laboratories in Sub-Saharan Africa.

Pitfalls of practicing cancer epidemiology in resource-limited settings: the case of survival and loss to follow-up after a diagnosis of Kaposi's sarcoma in five countries across sub-Saharan Africa.

BACKGROUND Survival after diagnosis is a fundamental concern in cancer epidemiology. In resource-rich settings, ambient clinical databases, municipal data and cancer registries make survival estimation in real-world populations relatively straightforward. In resource-poor settings, given the deficiencies in a variety of health-related data systems, it is less clear how well we can determine cancer survival from ambient data. METHODS We addressed this issue in sub-Saharan Africa for Kaposi's sarcoma (KS), a cancer for which incidence has exploded with the HIV epidemic but for which survival in the region may be changing with the recent advent of antiretroviral therapy (ART). From 33 primary care HIV Clinics in Kenya, Uganda, Malawi, Nigeria and Cameroon participating in the International Epidemiologic Databases to Evaluate AIDS (IeDEA) Consortia in 2009-2012, we identified 1328 adults with newly diagnosed KS. Patients were evaluated from KS diagnosis until death, transfer to another facility or database closure. RESULTS Nominally, 22% of patients were estimated to be dead by 2 years, but this estimate was clouded by 45% cumulative lost to follow-up with unknown vital status by 2 years. After adjustment for site and CD4 count, age <30 years and male sex were independently associated with becoming lost. CONCLUSIONS In this community-based sample of patients diagnosed with KS in sub-Saharan Africa, almost half became lost to follow-up by 2 years. This precluded accurate estimation of survival. Until we either generally strengthen data systems or implement cancer-specific enhancements (e.g., tracking of the lost) in the region, insights from cancer epidemiology will be limited.

Malaria prevention in Kenyan women of childbearing age

The objective of this program is to reduce malaria incidence in Kenya. Malaria poses a large public health challenge in Kenya, and although public health efforts have traditionally been focused on treatment of infected patients, due to increased drug resistance and lack of drug-adherence, prevention strategies are needed. This program targets Kenyan women, the likely caretakers in the home, and promotes malaria prevention behaviors through health education. ^ A planning group will be assembled and a needs assessment will be performed, verifying risk factors and conditions associated with malaria, as well as personal and external determinants. Behavioral and environmental outcomes will be determined, and performance objectives for each outcome will be established. Matrices of change objectives will be created, and detailed methods and strategies will be linked to each change objective. Program elements include media, education, and incentives. All materials used in this program will be subjected to pre-test to ensure cultural relevance and fidelity. Matrices of change objectives will be created for program adopters and implementers, as well as correlating methods and strategies associated with each change objective. Performance objectives will also be compiled for program maintainers. A program evaluation plan will follow "Pre-Post Comparison Group" design. Outcome evaluation and process evaluation will be conducted. The sample population will be screened based on age and gender so as to maintain comparability to the target population. Measurements will be taken before the program to establish baseline, directly following the program to determine short-term effects, and three months after the program is completed to determine long-term effects. ^ One limitation of this program is selection bias, due to the nature of quasi-experimental studies. Thorough screening prior to sample selection will minimize selection bias and ensure group homogeneity. Another limitation is attrition, and this will be minimized where possible through the use of incentives. In cases where loss to follow-up is not avoidable, such as death or natural disasters, the attrition effect will be estimated using structural equation modeling after reviewing the sample size, differential attrition and total attrition. ^ This intervention is based heavily on health promotion theories, but it is important to remember that in the field, the program plan will likely include only the necessary practical strategies. The target population, Kenyan women of childbearing age, will be significant in decreasing the malaria disease burden in Kenya.^