Back

Filovirus Evidence Maps: A community resource to identify and curate the published evidence on immunity and vaccination for BDBV, EBOV, MARV, and SUDV

Chung, Y.; Bailey, B. A.; Bowden-Reif, E.; Csolle, M.; Docken, S. S.; Jachno, K.; Khoury, D. S.; McDonald, S.; Pattuwage, L.; White, H.; Zazryn, T.; Turner, T.; Davenport, M. P.

2026-05-24 infectious diseases
10.64898/2026.05.22.26353826 medRxiv
Show abstract

Filoviruses pose a threat to individuals and the global community as pathogens of pandemic potential. The scientific community faces an ongoing challenge of developing effective vaccines with unpredictable outbreaks concentrated in countries with lower healthcare resources. Given these limitations, it is important to ensure that existing filovirus research is used as efficiently as possible. To enable rapid identification and use of this research, we have developed evidence maps of existing filovirus publications to enable further analysis and synthesis. We systematically identified and categorised existing immunological and clinical publications on Bundibugyo (BDBV), Marburg (MARV), Sudan (SUDV) and Ebola (EBOV) viruses. We captured studies that reported on animal or human immune responses to infection, outcome of infection, or human vaccine safety data. Initial searches of PubMed, Embase and Europe PMC were run between November 2024 and January 2025 and the MARV, SUDV and EBOV searches were updated on 1 August 2025. A BDBV search was conducted on 18 May 2026 in response to the WHO declaration of a Public Health Emergency on 17 May 2026. The initial searches retrieved 208, 1646, 534 and 3963 manuscripts for BDBV, MARV, SUDV and EBOV, respectively. After screening using an a priori exclusion criteria, 49 BDBV, 198 MARV, 149 SUDV and 850 EBOV publications were included on each evidence map. These maps provide a comprehensive, transparent and reproducible structure to categorise existing studies of filovirus vaccination and immunity. They allow rapid identification of the totality of available evidence and the existing experimental tools to support vaccine development for these priority pathogens.

Matching journals

The top 12 journals account for 50% of the predicted probability mass.

1
The Lancet Infectious Diseases
71 papers in training set
Top 0.1%
14.1%
2
PLOS Biology
408 papers in training set
Top 0.5%
8.2%
3
Nature Communications
4913 papers in training set
Top 34%
4.8%
4
Nature Medicine
117 papers in training set
Top 0.6%
4.2%
5
Scientific Data
174 papers in training set
Top 0.5%
3.6%
6
Vaccine
189 papers in training set
Top 0.9%
3.0%
7
Vaccines
196 papers in training set
Top 0.8%
2.7%
8
Frontiers in Immunology
586 papers in training set
Top 3%
2.6%
9
Clinical Infectious Diseases
231 papers in training set
Top 2%
2.4%
10
The Journal of Infectious Diseases
182 papers in training set
Top 2%
2.0%
11
Nature
575 papers in training set
Top 10%
2.0%
12
PLOS ONE
4510 papers in training set
Top 48%
2.0%
50% of probability mass above
13
New England Journal of Medicine
50 papers in training set
Top 0.4%
2.0%
14
PLOS Neglected Tropical Diseases
378 papers in training set
Top 3%
1.7%
15
Science Translational Medicine
111 papers in training set
Top 3%
1.7%
16
Eurosurveillance
80 papers in training set
Top 0.8%
1.6%
17
The Lancet Microbe
43 papers in training set
Top 0.7%
1.6%
18
npj Vaccines
62 papers in training set
Top 0.3%
1.6%
19
Science
429 papers in training set
Top 16%
1.5%
20
Journal of Virology
456 papers in training set
Top 2%
1.3%
21
Med
38 papers in training set
Top 0.4%
1.3%
22
Clinical Microbiology and Infection
60 papers in training set
Top 0.7%
1.3%
23
PLOS Pathogens
721 papers in training set
Top 7%
1.3%
24
eBioMedicine
130 papers in training set
Top 2%
1.2%
25
Journal of Travel Medicine
18 papers in training set
Top 0.2%
1.2%
26
Annals of Internal Medicine
27 papers in training set
Top 0.6%
1.2%
27
BMC Medicine
163 papers in training set
Top 5%
1.1%
28
Scientific Reports
3102 papers in training set
Top 69%
0.9%
29
Virus Evolution
140 papers in training set
Top 1%
0.9%
30
Journal of Medical Virology
137 papers in training set
Top 3%
0.9%