Nodding Syndrome is a poorly understood neurologic disorder of unknown aetiology that affects children and adolescents in Africa. Recent studies have suggested that the head nods are due to atonic seizures and Nodding Syndrome may be classified as probably symptomatic generalised epilepsy. As part of the Ugandan Ministry of Health clinical management response, a multidisciplinary team developed a manual to guide the training of health workers with knowledge and skills to manage the patients. In the absence of a known cause, it was decided to offer symptomatic care. The objective is to relieve symptoms, offer primary and secondary prevention for disability and rehabilitation to improve function. Initial management focuses on the most urgent needs of the patient and the immediate family until 'stability' is achieved. The most important needs were considered as seizure control, management of behavioural and psychiatric difficulties, nursing care, nutritional and subsequently, physical and cognitive rehabilitation. This paper summarises the processes by which the proposed guidelines were developed and provides an outline of the specific treatments currently being provided for the patients.
BackgroundDisease surveillance in rural regions of many countries is poor, such that prolonged delays (months) may intervene between appearance of disease and its recognition by public health authorities. For infectious disorders, delayed recognition and intervention enables uncontrolled disease spread. We tested the feasibility in northern Uganda of developing real-time, village-based health surveillance of an epidemic of Nodding syndrome (NS) using software-programmed smartphones operated by minimally trained lay mHealth reporters.Methodology and principal findingsWe used a customized data collection platform (Magpi) that uses mobile phones and real-time cloud-based storage with global positioning system coordinates and time stamping. Pilot studies on sleep behavior of U.S. and Ugandan medical students identified and resolved Magpi-programmed cell phone issues. Thereafter, we deployed Magpi in combination with a lay-operator network of eight mHealth reporters to develop a real-time electronic map of child health, injury and illness relating to NS in rural northern Uganda. Surveillance data were collected for three consecutive months from 10 villages heavily affected by NS. Overall, a total of 240 NS-affected households and an average of 326 children with NS, representing 30 households and approximately 40 NS children per mHealth reporter, were monitored every week by the lay mHealth team. Data submitted for analysis in the USA and Uganda remotely pinpointed the household location and number of NS deaths, injuries, newly reported cases of head nodding (n = 22), and the presence or absence of anti-seizure medication.Conclusions and significanceThis study demonstrates the feasibility of using lay mHealth workers to develop a real-time cartography of epidemic disease in remote rural villages that can facilitate and steer clinical, educational and research interventions in a timely manner.
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