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.