2.1 Identification of studies for review
We identified 839 studies from electronic search of five databases. After removing duplicates, we screened the titles and abstracts of 493 published articles and excluded 464 studies. We retrieved the full texts of the remaining 29 studies and excluded 12 of these studies 1, 7, 12, 18-26 because they either did not report on the yellow fever burden or were from non-African countries. From the 17 studies that reported on yellow fever incidence, we excluded five more studies 21, 24-27 because they only reported on the evaluation of yellow fever vaccine without reporting data on yellow fever burden. We finally included 12 studies (Figure 2).2, 31-41
2.2 Characteristics of included studies
A summary table of characteristics of the included studies is presented in the appendices (Supplementary Table 2) We categorized studies based on year of assessment, test methods implemented for confirming the diagnosis of yellow fever, and clinical case definition used. The number of studies published each year increased modestly from 1975 to 2018. Although studies originated from eight African countries, three studies were from Nigeria 32-34, two studies each from Senegal 36, 37 and Uganda 38, 41 and one study from each of the five countries, Kenya 35, Ethiopia 39, Ghana 31, Gambia 2 and DRC 40. The majority of studies ‘Seven’, were from West Africa 2,31-37 ‘Three’ studies from East Africa 35, 38, 41, ‘One’ from North Eastern Africa 39 and ‘One’ studies from Central Africa.40 All the three modes of yellow fever transmission considered in this review were reported by at least one study. Eight studies reported that the outbreak was due to sylvatic mode of transmission 2, 32, 35-39, 41, two studies reported that it was due to an urban mode of transmission 33, 40 and only one study reported the intermediate mode of transmission.39
Ten of the studies 2, 31-34, 36-41 were reported from hospital and field-based surveillance studies while two studies35, 38 were only in-hospital-based surveillance studies. Nine studies2, 31-34, 36, 37, 39, 41 included participants of all ages while four studies reported the disease in specific age groups such as from 10-70 years 35, 3 months -83 years38, 3-64 years41 and 10-72 years40, respectively. Nine of the included studies 2, 31, 34-39, 41 were conducted in rural areas, two 33, 40 in urban areas and one 39 in mixed rural/urban setting. The population was reported in all the studies to live on subsistence farming, growing several crops and rearing livestock as well. Most of the people practice domestic water storage except for one of the studies 37 that reported that the people practice less livestock rearing and less domestic water storage while one of the studies40 did not report on any of the above. Rainy season and increased breeding sites were reported in all the studies to be a risk factor for yellow fever epidemic as these can increase the mosquito population. However, two studies36,41 did not attribute the outbreak to the rains but reported that the people were in contact with the forest after returning from the Internally Displaced Persons camps, having to clean their homes when they returned after two years and the multiple natural breeding sites for mosquitoes, respectively, led to the outbreak. All the included studies also reported that yellow fever was confirmed using viral serology by doing ELISA and identifying IgM to yellow fever virus, and virus isolation. Some of the studies for instance 33, 35 reported that histopathology on liver specimens were done. One study, 31 reported that test for antibody neutralization was not done.
The duration of the outbreak lasted for 11 months in Ethiopia 39 followed by Gambia which lasted for 8 months.2 Outbreaks in DRC 40, Kenya 35, and Nigeria 32 lasted for 7, 6 and 5 months, respectively. One of the studies reported from Nigeria 33 recorded that the outbreak lasted for 4 months. One study from Senegal36 reported 2 months while the other study from Senegal37 reported only one month. The other studies reported that the outbreak lasted for 3 months 33, 36, 37, while the study done in Ghana did not report the duration of the outbreak.31
2.3 Assessment of risk of bias of included studies.
We evaluated all the studies in ten different domains using the risk of bias tool16 and our summary assessment was low risk of bias for ten studies (83.33%) 2, 32-39, 41 and moderate risk of bias for 2 studies (16.67%) (Supplementary Table 3).
2.4 Incidence of Yellow Fever
Meta-analysis of yellow fever incidence estimates from different studies and countries resulted in significant heterogeneity (I2=99.4%, P<0.001, Figure 3) and therefore we report narrative results per study. The two studies from Uganda found very low incidence of less than 3 and 13 cases per 100,000 population respectively, Kenya <30 cases per 100,000, Ethiopian 40 cases per 100,000, In Gambia < 50 cases per 100,000, Nigeria the incidence ranged from <1 to over 80 cases per 100,000 population. The two studies in Senegal found incidence rates of approximately 1,300 and 5,900 cases per 100,000 population while Ghana found the highest incidence which ranged between 320 to over 10,000 cases per 100,000 population (Figure 3).
2.5 Case Fatality Rate
Meta-analysis of CFR (in %) resulted in significant heterogeneity (I2=95.6%, P<0.001, Figure 3) and therefore we report results narratively per study. The only study from DRC had the lowest CFR of just over 10%. The Ethiopian study found a CFR of slightly over 30%, the two studies from Uganda found CFRs of just over 30% each, while the one study from Gambia found a CFR of less than 30%. The CFRs in different regions of Ghana ranged from just over 16% in Volta Region to almost 40% in Brong Ahafo. The two Senegal studies found high CFRs of 28% and 42%, while the Kenyan study found a higher CFR of over 60%. Lastly, the Nigerian studies found varying CFRs from 11% to 85% (Figure 4).
2.6 Mortality Rate
We could not perform meta-analysis of mortality rate because the population sizes were not reported by most included studies. The results also differed widely such that a meta-analysis would likely result in high heterogeneity. We therefore reported the results narratively for each study. The two studies from Senegal had high mortality rates ranging from over 500 to almost 1,700 deaths per 100,000. The Ethiopian and Kenyan single studies had low mortality rates of 12 and 17 deaths per 100,000 population. In Uganda, the mortality rates were even lower, ranging from less than 1 to 4 deaths per 100,000 population. In Gambia, it was 12 deaths per 100,000 population. In Ghana, the mortality rate ranged from just over 50 in Volta Region to over 2,200 deaths per 100,000 population in the Eastern Region. The one study in DRC found a low mortality rate of 1 death per 100,000 population. Lastly, the studies from Nigeria found mortality rates ranging from 0.2 deaths per 100, 000 population in Kwara State to more than 44 deaths per 100,000 population in South Eastern Nigeria.