| Literature DB >> 34635069 |
Terna Nomhwange1, Anne Eudes Jean Baptiste2, Obi Ezebilo3, Joseph Oteri4, Lois Olajide5, Kizito Emelife4, Shehu Hassan4, Erdoo R Nomhwange6, Kennedy Adejoh7, Faith Ireye7, Eyo E Nora7, Adamu Ningi7, Blaise Bathondeli8, Oyewale Tomori9.
Abstract
BACKGROUND: Yellow fever outbreaks are documented to have a considerable impact not only on the individuals but on the health system with significant economic implications. Efforts to eliminate yellow fever outbreaks globally through the EYE strategy remains important following outbreaks in Africa, Nigeria included. The outbreaks reported in Nigeria, since 2017 and the response efforts provide an opportunity to document and guide interventions for improving future outbreaks in Nigeria and other countries in Africa.Entities:
Keywords: Arboviruses; EYE strategy; VPD outbreaks; Vaccination; Yellow fever
Mesh:
Year: 2021 PMID: 34635069 PMCID: PMC8504075 DOI: 10.1186/s12879-021-06727-y
Source DB: PubMed Journal: BMC Infect Dis ISSN: 1471-2334 Impact factor: 3.090
Fig. 1Algorithm for the confirmation of yellow fever cases in Nigeria
Age and sex distribution of suspected yellow fever cases reported and cumulated age group proportions in Nigeria between September 2017 and 2 September 2019
| Age Group | Male | Female | Total | Age proportion (%) | Cumulative proportion (%) | Female:male ratio |
|---|---|---|---|---|---|---|
| < 1 year | 12 (57%) | 9 (43%) | 21 | 0 | 0 | 1.3:1 |
| 1–5 years | 993 (62%) | 617 (38%) | 1610 | 20 | 20 | 1.6:1 |
| 6–10 years | 821 (61%) | 527 (39%) | 1348 | 17 | 37 | 1.6:1 |
| 11–15 years | 522 (61%) | 338 (39%) | 860 | 11 | 48 | 1.5:1 |
| 16–20 years | 505 (54%) | 429 (46%) | 934 | 12 | 60 | 1.2:1 |
| 21–25 years | 462 (53%) | 410 (47%0 | 872 | 11 | 71 | 1.1:1 |
| 26–30 years | 360 (52%) | 332 (48%) | 692 | 9 | 80 | 1.1:1 |
| 31–35 years | 211 (52%) | 198 (48%) | 409 | 5 | 85 | 1.1:1 |
| 36–40 years | 205 (56%) | 158 (44%) | 363 | 5 | 90 | 1.3:1 |
| 41–45 years | 120(58%) | 88 (42%) | 208 | 3 | 93 | 1.4:1 |
| 46–50 years | 100(53%) | 90 (47%) | 190 | 2 | 95 | 1.1:1 |
| 51–55 years | 50 (55%) | 41 (45%) | 91 | 1 | 96 | 1.2:1 |
| 56–60 years | 54 (57%) | 40 (43%) | 94 | 1 | 97 | 1.4:1 |
| 61 years + | 80 (52%) | 74 (48%) | 154 | 2 | 99 | 1.1:1 |
| Unknown/missing | 33 (69%) | 15 (31%) | 48 | 1 | 100 | 2.2:1 |
| Total | 4528 (57%) | 3366 (43%) | 7894 | 100 | 1.3:1 |
*Descriptive statistics: Mean = 19.3 standard error = 0.17 median = 16 mode = 4 standard deviation = 15.4 range = 0–92 confidence level (95.0%) = 0.34
Fig. 2Epidemic curve showing laboratory-confirmed cases of yellow fever by month in Nigeria between September 2017–*2019
Fig. 3Map showing areas with yellow fever outbreaks in September 2017–2019 and epidemic blocks and spread in Nigeria. *Suspected and confirmed Yellow fever spatial distribution by state and LGA/District with clustering of outbreaks in identified epidemic blocks
Fig. 4Bar chart showing average duration for various phases of the yellow fever detection and response by year and ICG application 2017–2019
Fig. 5Case fatality rate of yellow fever by state and zone in Nigeria between 2017 and 2019
Fig. 6Trend line showing reported and confirmed yellow fever cases and vaccination campaigns in Nigeria between September 2017–2019
Summary of vaccination interventions conducted in response to the yellow fever outbreak in Nigeria 2017–2019 through reactive and preventive campaigns in the four identified Epidemic blocks
| Epid. Block | State | ICG requests and reactive vaccinations | Preventive mass vaccination campaigns (PMVC) | Total Vaccinated | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Implementation months | Total reactive vaccinations | Post campaign coverage survey | Nov-18 | Feb-18 | Oct–Dec 2019 | Total PMVC vaccinations | Post campaign coverage survey | ||||
| Block 1 | FCT | 3,269,041 | 3,269,041 | 96% | 3,269,041 | 29,357,509 | |||||
| Katsina | Aug-18 | 154,131 | 74% | 6,720,113 | 6,720,113 | 84% | 6,874,244 | ||||
| Kebbi | Mar-18 | 1,525,308 | 89% | 2,283,993 | 2,283,993 | 62% | 3,809,301 | ||||
| Kogi | Nov-17 | 776,995 | 92% | 3,153,422 | 3,153,422 | 92% | 3,930,417 | ||||
| Kwara | Nov-17 | 1,025,727 | 87% | 1,884,065 | 1,884,065 | 85% | 2,909,792 | ||||
| Niger | Mar-18 | 1,222,506 | 91% | 4,342,518 | 4,342,518 | 78% | 5,565,024 | ||||
| Sokoto | Mar-18 | 191,239 | 87% | 2,808,451 | 2,808,451 | 69% | 2,999,690 | ||||
| Block 2 | Delta | Jul-19 | 431,164 | 73% | 0 | 431,164 | 7,814,903 | ||||
| Edo | Jul-19 | 2,176,515 | 64% | 0 | 2,176,515 | ||||||
| Zamfara | Dec-17 | 1,250,404 | 80% | 2,767,267 | 2,767,267 | 80% | 4,017,671 | ||||
| Ondo | Jul-19 | 1,189,553 | 87% | 0 | 1,189,553 | ||||||
| Block 3 | Benue | Aug-19 | 710,308 | 78.% | 0 | 710,308 | 1,854,461 | ||||
| Cross River | Aug-19 | 129,713 | NA | 0 | 129,713 | ||||||
| Ebonyi | Aug-19 | 1,014,440 | NA | 0 | 1,014,440 | ||||||
| Block 4 | Bauchi** | 407,708 | 0 | 407,708 | 6,621,370 | ||||||
| Borno* | 0 | 983,982 | 524,378 | 1,508,360 | 78% | 1,508,360 | |||||
| Plateau | 0 | 4,705,302 | 4,705,302 | 94% | 4,705,302 | ||||||
| Total | 12,205,711 | 8,788,736 | 17,933,683 | 6,720,113 | 33,442,532 | 45,648,243 | |||||