Childhood disability in rural Niger: a population-based assessment using the Key Informant Method.

BACKGROUND: Data on childhood disability is essential for planning health, education and other services. However, information is lacking in many low- and middle-income countries, including Niger. This study uses the Key Informant Method, an innovative and cost-effective strategy for generating population-based estimates of childhood disability, to estimate the prevalence and causes of moderate/severe impairments and disabling health conditions in children of school-going age (7-16 years) in the Kollo department of western Niger. METHODS: Community-based key informants were trained to identify children who were suspected of having the impairment types/health conditions included in this study. Children identified by key informants were visited by paediatricians and underwent an assessment for moderate/severe vision, hearing, physical and intellectual impairments, as well as epilepsy, albinism and emotional distress. RESULTS: Two thousand, five hundred sixty-one children were identified by key informants, of whom 2191 were visited by paediatricians (response rate = 85.6%). Overall, 597 children were determined to have an impairment/health condition, giving a prevalence of disability of 11.4 per 1000 children (10.6- 12.2). Intellectual impairment was most common (6.5 per 1000), followed by physical (4.9 per 1000) and hearing impairments (4.7 per 1000). Many children had never sought medical attention for their impairment/health condition, with health seeking ranging from 40.0% of children with visual impairment to 67.2% for children with physical impairments. CONCLUSION: The Key Informant Method enabled the identification of a large number of children with disabling impairments and health conditions in rural Niger, many of whom have unmet needs for health and other services.

Cyber and Physical Security Vulnerability Assessment for IoT-Based Smart Homes.

The Internet of Things (IoT) is an emerging paradigm focusing on the connection of devices, objects, or "things" to each other, to the Internet, and to users. IoT technology is anticipated to become an essential requirement in the development of smart homes, as it offers convenience and efficiency to home residents so that they can achieve better quality of life. Application of the IoT model to smart homes, by connecting objects to the Internet, poses new security and privacy challenges in terms of the confidentiality, authenticity, and integrity of the data sensed, collected, and exchanged by the IoT objects. These challenges make smart homes extremely vulnerable to different types of security attacks, resulting in IoT-based smart homes being insecure. Therefore, it is necessary to identify the possible security risks to develop a complete picture of the security status of smart homes. This article applies the operationally critical threat, asset, and vulnerability evaluation (OCTAVE) methodology, known as OCTAVE Allegro, to assess the security risks of smart homes. The OCTAVE Allegro method focuses on information assets and considers different information containers such as databases, physical papers, and humans. The key goals of this study are to highlight the various security vulnerabilities of IoT-based smart homes, to present the risks on home inhabitants, and to propose approaches to mitigating the identified risks. The research findings can be used as a foundation for improving the security requirements of IoT-based smart homes.