Browsing by Author "Aceng, Jane R."

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    Is nodding syndrome an Onchocerca volvulus induced neuro-inflammatory disorder? Uganda's story of research in understanding the disease
    (International Journal of Infectious Diseases, 2016) Idro, Richard; Opar, Bernard; Wamala, Joseph; Abbo, Catherine; Onzivua, Sylvester; Mwaka, Deogratius Amos; Kakooza-Mwesige, Angelina; Mbonye, Anthony; Aceng, Jane R.
    Nodding syndrome is a devastating neurological disorder, mostly affecting children in eastern Africa. An estimated 10 000 children are affected. Uganda, one of the most affected countries, set out to systematically investigate the disease and develop interventions for it. On December 21, 2015, the Ministry of Health held a meeting with community leaders from the affected areas to disseminate the results of the investigations made to date. This article summarizes the presentation and shares the story of studies into this peculiar disease. It also shares the results of preliminary studies on its pathogenesis and puts into perspective an upcoming treatment intervention. Clinical and electrophysiological studies have demonstrated nodding syndrome to be a complex epilepsy disorder. A definitive aetiological agent has not been established, but in agreement with other affected countries, a consistent epidemiological association has been demonstrated with infection by Onchocerca volvulus. Preliminary studies of its pathogenesis suggest that nodding syndrome may be a neuroinflammatory disorder, possibly induced by antibodies to O. volvulus cross-reacting with neuron proteins. Histological examination of post-mortem brains has shown some yet to be characterized polarizable material in the majority of specimens. Studies to confirm these observations and a clinical trial are planned for 2016.
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    Is Nodding Syndrome an Onchocerca Volvulus-Induced Neuroinflammatory Disorder? Uganda’s Story of Research in Understanding the Disease
    (International Journal of Infectious Diseases, 2016) Idro, Richard; Opar, Bernard; Wamala, Joseph; Abbo, Catherine; Onzivua, Sylvester; Mwaka, Deogratius Amos; Kakooza-Mwesige, Angelina; Mbonye, Anthony; Aceng, Jane R.
    The Sustainable Development Goals (SDGs) mandate systematic monitoring of the health and wellbeing of all children to achieve optimal early childhood development. However, global epidemiological data on children with developmental disabilities are scarce. The Global Burden of Diseases, Injuries, and Risk Factors Study 2016 provides a comprehensive assessment of prevalence and years lived with disability (YLDs) for development disabilities among children younger than 5 years in 195 countries and territories from 1990 to 2016.
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    The Ugandan Severe Acute Respiratory Syndrome -Coronavirus 2 (SARS-CoV-2) Model: A Data Driven Approach to Estimate Risk
    (medRxiv, 2020) Nannyonga, Betty; Kyobe Bosa, Henry; Woldermariam, Yonas T.; Kaleebu, Pontiano; Ssenkusu, John M.; Lutalo, Tom; Kirungi, Willford; Makumbi, Fredrick E.; Ssembatya, Vincent A.; Mwebesa, Henry G.; Atwine, Diana; Aceng, Jane R.; Wanyenze, Rhoda K.
    The first case of Severe Acute Respiratory Syndrome-Coronavirus 2 (SARS-CoV-2) was identified on March 21, 2020, in Uganda. The number of cases increased to 8,287 by September 30, 2020. By May throughout June, most of the cases were predominantly imported cases of truck drivers from neighbouring countries. Uganda responded with various restrictions and interventions including lockdown, physical distancing, hand hygiene, and use of face masks in public, to control the growth rate of the outbreak. By end of September 2020, Uganda had transitioned into community transmissions and most of the reported cases were locals contacts and alerts. This study assessed risks associated with SARS-CoV-2 in Uganda, and presents estimates of the reproduction ratio in real time. An optimal control analysis was performed to determine how long the current mitigation measures such as controlling the exposure in communities, rapid detection, confirmation and contact tracing, partial lockdown of the vulnerable groups and control at the porous boarders, could be implemented and at what cost. Methods: The daily confirmed cases of SARS-CoV-2 in Uganda were extracted from publicly available sources. Using the data, relative risks for age, gender, and geographical location were determined. Four approaches were used to forecast SARS-CoV-2 in Uganda namely linear exponential, nonlinear exponential, logistic and a deterministic model.