Malaria elimination in Zanzibar: where next?

In 2018, Zanzibar developed a national malaria strategic plan IV (2018-2023) to guide elimination of malaria by 2023. We assessed progress in the implementation of malaria activities as part of the end-term review of the strategic plan. The review was done between August and October 2022 following the WHO guideline to assess progress made towards malaria elimination, effectiveness of the health systems in delivering malaria case management; and malaria financing. A desk review examined available malaria data, annual work plans and implementation reports for evidence of implemented malaria activities. This was complemented by field visits to selected health facilities and communities by external experts, and interviews with health management teams and inhabitants to authenticate desk review findings. A steady increase in the annual parasite incidence (API) was observed in Zanzibar, from 2.7 (2017) to 3.6 (2021) cases per 1,000 population with marked heterogeneity between areas. However, about 68% of the detected malaria cases were imported into Zanzibar. Malaria case follow-up and investigation increased from <70% in 2017 to 94% and 96% respectively, in 2021. The review noted a 3.7-fold increase of the health allocation in the country's budget, from 31.7 million USD (2017/18) to 117.3 million USD (2022/23) but malaria allocation remained low (<1%). The varying transmission levels in the islands suggest a need for strategic re-orientation of the elimination attempts from a national-wide to a sub-national agenda. We recommend increasing malaria allocation from the health budget to ensure sustainability of malaria elimination interventions

New filovirus disease classification and nomenclature

Filoviruses, the members of the family Filoviridae, are currently classified into one proposed and five established genera (Supplementary Table 1). Of the twelve described filoviruses, six have been identified as aetiological agents of naturally occurring human disease outbreaks

Ebola haemorrhagic fever among hospitalised children and adolescents in nothern Uganda : Epidemiologic and clinical observations

Background : A unique feature of previous Ebola outbreaks has been the relative sparing of children. For the first time, an out break of an unusual illness-Ebola haemorrhagic fever occurred in Northern Uganda - Gulu district. Objectives : To describe the epidemiologic and clinical aspects of hospitalised children and adolescents on the isolation wards. Methods : A retrospective descriptive survey of hospital records for hospitalised children and adolescents under 18 years on the isolation wards in Gulu, Northern Uganda was conducted. All patient test notes were consecutively reviewed and non was excluded because being deficient. Results : Analysis revealed that 90 out of the 218 national laboratory confirmed Ebola cases were children and adolescents with a case fatality of 40%. The mean age was 8.2 years ± SD 5.6 with a range of 16.99 years. The youngest child on the isolation wards was 3 days old. The under fives contributed the highest admission (35%) among children and adolescents; and case fatality because of prolonged close contact with the seropositive relatives among the laboratory confirmed cases. All (100%) Ebola positive children and adolescents were febrile while only 16% had haemorragic manifestations. Conclusion : Similar to previous Ebola outbreaks, a relative sparing of children in this outbreak was observed. The under fives were at an increased risk of contact with the sick and dying. Recommendations : Strategies to shield children from exposure to dying and sick Ebola relatives are recommended in the event of future Ebola outbreaks. Health education to children and adolescents to avoid contact with sick and their body fluids should be emphasized. African Health Sciences 2001; 1(2): 60-6

Spatial and temporal distribution of infectious disease epidemics, disasters and other potential public health emergencies in the World Health Organisation Africa region, 2016-2018

Background Emerging and re-emerging diseases with pandemic potential continue to challenge fragile health systems in Africa, creating enormous human and economic toll. To provide evidence for the investment case for public health emergency preparedness, we analysed the spatial and temporal distribution of epidemics, disasters and other potential public health emergencies in the WHO African region between 2016 and 2018. Methods We abstracted data from several sources, including: the WHO African Region’s weekly bulletins on epidemics and emergencies, the WHO-Disease Outbreak News (DON) and the Emergency Events Database (EM-DAT) of the Centre for Research on the Epidemiology of Disasters (CRED). Other sources were: the Program for Monitoring Emerging Diseases (ProMED) and the Global Infectious Disease and Epidemiology Network (GIDEON). We included information on the time and location of the event, the number of cases and deaths and counter-checked the different data sources. Data analysis We used bubble plots for temporal analysis and generated graphs and maps showing the frequency and distribution of each event. Based on the frequency of events, we categorised countries into three: Tier 1, 10 or more events, Tier 2, 5–9 events, and Tier 3, less than 5 or no event. Finally, we compared the event frequencies to a summary International Health Regulations (IHR) index generated from the IHR technical area scores of the 2018 annual reports. Results Over 260 events were identified between 2016 and 2018. Forty-one countries (87%) had at least one epidemic between 2016 and 2018, and 21 of them (45%) had at least one epidemic annually. Twenty-two countries (47%) had disasters/humanitarian crises. Seven countries (the epicentres) experienced over 10 events and all of them had limited or developing IHR capacities. The top five causes of epidemics were: Cholera, Measles, Viral Haemorrhagic Diseases, Malaria and Meningitis. Conclusions The frequent and widespread occurrence of epidemics and disasters in Africa is a clarion call for investing in preparedness. While strengthening preparedness should be guided by global frameworks, it is the responsibility of each government to finance country specific needs. We call upon all African countries to establish governance and predictable financing mechanisms for IHR implementation and to build resilient health systems everywhere

Exposure patterns driving Ebola transmission in West Africa: A retrospective observational study.

Background The ongoing West African Ebola epidemic began in December 2013 in Guinea, probably from a single zoonotic introduction. As a result of ineffective initial control efforts, an Ebola outbreak of unprecedented scale emerged. As of 4 May 2015, it had resulted in more than 19,000 probable and confirmed Ebola cases, mainly in Guinea (3,529), Liberia (5,343), and Sierra Leone (10,746). Here, we present analyses of data collected during the outbreak identifying drivers of transmission and highlighting areas where control could be improved. Methods and Findings Over 19,000 confirmed and probable Ebola cases were reported in West Africa by 4 May 2015. Individuals with confirmed or probable Ebola ("cases") were asked if they had exposure to other potential Ebola cases ("potential source contacts") in a funeral or non-funeral context prior to becoming ill. We performed retrospective analyses of a case line-list, collated from national databases of case investigation forms that have been reported to WHO. These analyses were initially performed to assist WHO's response during the epidemic, and have been updated for publication. We analysed data from 3,529 cases in Guinea, 5,343 in Liberia, and 10,746 in Sierra Leone; exposures were reported by 33% of cases. The proportion of cases reporting a funeral exposure decreased over time. We found a positive correlation (r = 0.35, p &lt; 0.001) between this proportion in a given district for a given month and the within-district transmission intensity, quantified by the estimated reproduction number (R). We also found a negative correlation (r = −0.37, p &lt; 0.001) between R and the district proportion of hospitalised cases admitted within ≤4 days of symptom onset. These two proportions were not correlated, suggesting that reduced funeral attendance and faster hospitalisation independently influenced local transmission intensity. We were able to identify 14% of potential source contacts as cases in the case line-list. Linking cases to the contacts who potentially infected them provided information on the transmission network. This revealed a high degree of heterogeneity in inferred transmissions, with only 20% of cases accounting for at least 73% of new infections, a phenomenon often called super-spreading. Multivariable regression models allowed us to identify predictors of being named as a potential source contact. These were similar for funeral and non-funeral contacts: severe symptoms, death, non-hospitalisation, older age, and travelling prior to symptom onset. Non-funeral exposures were strongly peaked around the death of the contact. There was evidence that hospitalisation reduced but did not eliminate onward exposures. We found that Ebola treatment units were betterthan other health care facilities at preventing exposure from hospitalised and deceased individuals. The principal limitation of our analysis is limited data quality, with cases not being entered into the database, cases not reporting exposures, or data being entered incorrectly (especially dates, and possible misclassifications). Conclusions Achieving elimination of Ebola is challenging, partly because of super-spreading. Safe funeral practices and fast hospitalisation contributed to the containment of this Ebola epidemic. Continued real-time data capture, reporting, and analysis are vital to track transmission patterns, inform resource deployment, and thus hasten and maintain elimination of the virus from the human population.</p