Table 1.
Principal findings of outbreak prediction articles, by disease
| All diseases | Rift Valley fever | Zika disease | CCHF | Ebola and Marburg disease | Lassa fever | MERS | Nipah and Henipa virus | SARS | |
| Number of articles (%) | 58 (100) | 21 (36) | 13 (22) | 8 (14) | 6 (10) | 5 (9) | 4 (7) | 2 (3) | 2 (3) |
| Date range | |||||||||
| 2010–2019 | 47 (81) | 15 | 13 | 6 | 5 | 4 | 4 | 2 | |
| 2000–2009 | 9 (16) | 4 | 2 | 1 | 1 | 2 | |||
| 1990–1999 | 2 (3) | 2 | |||||||
| Region of study | |||||||||
| African continent | 28 (48) | 18 | 1 | 6 | 5 | ||||
| Asia-Pacific | 4 (7) | 3 | 1 | ||||||
| Europe | 3 (5) | 1 | 1 | 1 | 1 | ||||
| Middle East | 9 (16) | 2 | 6 | 1 | |||||
| North America | 2 (3) | 1 | 1 | ||||||
| Latin America and Caribbean* | 5 (9) | 5 | |||||||
| Global | 8 (14) | 1 | 3 | 2 | 2 | ||||
| Prediction methodology | |||||||||
| Risk mapping | 26 (45) | 14 | 6 | 1 | 3 | 2 | 1 | 1 | |
| Regression model | 21 (36) | 7 | 5 | 4 | 3 | 1 | 1 | ||
| Time series forecasting | 23 (40) | 9 | 5 | 4 | 2 | 1 | 2 | ||
| Qualitative | 7 (12) | 4 | 2 | 2 | 1 | 1 | |||
| Other quantitative | 9 (16) | 1 | 2 | 1 | 1 | 2 | 1 | 1 | 2 |
| Species niche model | 15 (26) | 3 | 4 | 1 | 5 | 3 | 1 | ||
| Machine learning | 16 (28) | 3 | 6 | 2 | 2 | 2 | 1 | ||
| Spatiotemporal model | 25 (43) | 13 | 4 | 4 | 2 | 2 | |||
| Internet/phone/computer† | 6 (10) | 5 | 1 | ||||||
| Early warning system** | 17 (29) | 7 | 5 | 3 | 1 | 1 | |||
| Incidence modelling | 11 (19) | 5 | 5 | 1 | |||||
| Model type | |||||||||
| Deterministic | 6 (10) | 2 | 1 | 1 | 1 | 1 | |||
| Stochastic | 35 (60) | 11 | 9 | 6 | 3 | 3 | 2 | 1 | |
| Mixed | 6 (10) | 1 | 1 | 1 | 2 | 1 | 2 | ||
| Not applicable/not stated | 11 (19) | 7 | 2 | 1 | 1 | 1 | |||
| Data sources | |||||||||
| Case data | 47 (81) | 12 | 12 | 7 | 6 | 5 | 3 | 2 | 2 |
| Other patient health data | 13 (22) | ||||||||
| Meteorological/climate | 39 (67) | 19 | 7 | 5 | 4 | 3 | 1 | ||
| Vector/host | 31 (53) | 13 | 7 | 4 | 5 | 3 | 1 | ||
| Sociodemographic | 24 (41) | 7 | 7 | 3 | 3 | 2 | 2 | 1 | 1 |
| Behaviour (way of infection) | 8 (14) | 2 | 1 | 1 | 1 | 2 | 1 | ||
| Healthcare | 5 (9) | 1 | 2 | 1 | 1 | 1 | 1 | ||
| Transportation | 12 (21) | 2 | 4 | 1 | 2 | 2 | 1 | 2 | |
| Internet† | 7 (12) | 1 | 5 | 1 | |||||
| Geographical | 32 (55) | 15 | 13 | 6 | 5 | 4 | 4 | 2 | |
| Economic | 9 (16) | 2 | 4 | 1 | 1 | 2 | 1 | ||
| Ecological | 18 (31) | 9 | 3 | 2 | 4 | 2 | |||
| Expert opinion | 5 (9) | 4 | 1 | 1 | |||||
| Other‡ | 6 (10) | 1 | 1 | 1 | 3 | 2 | |||
| Prediction outcome | |||||||||
| Future cases | 21 (36) | 1 | 9 | 5 | 1 | 3 | 2 | ||
| Outbreak risk factors | 37 (64) | 19 | 4 | 7 | 6 | 3 | 1 | ||
| Immunity parameters§ | 7 (12) | 2 | 1 | 1 | 1 | 2 | |||
| Risk maps | 29 (50) | 4 | 2 | 1 | 1 | 2 | |||
| Spatial prediction | 44 (76) | 19 | 10 | 5 | 4 | 4 | 1 | 1 | 2 |
| Temporal prediction | 39 (67) | 15 | 7 | 6 | 4 | 2 | 3 | 1 | 1 |
| Outbreak risk | 36 (62) | 14 | 9 | 3 | 5 | 3 | 2 | 2 | 1 |
| Spillover events | 6 (10) | 2 | 2 | 3 | 2 | ||||
| Bio-Env-Econ consequences¶ | 4 (7) | 3 | 1 | 1 | |||||
| Env transmission suitability | 20 (34) | 10 | 4 | 2 | 4 | 2 | 1 | ||
| Population at risk | 8 (14) | 3 | 2 | 2 | 3 | ||||
| Introduction risk | 5 (9) | 1 | 2 | 2 | 1 | 1 | 1 | ||
| Effect of climate change | 3 (5) | 2 | |||||||
| Epidemic dynamics | 17 (29) | 3 | 4 | 4 | 2 | 1 | 2 | 1 | |
| Implementation of prediction/methods by decision makers | |||||||||
| Yes | 6 (10) | 4 | 1 | 1 | |||||
| Suggested | 30 (52) | 10 | 4 | 6 | 4 | 4 | 3 | 1 | 1 |
| No | 22 (38) | 7 | 8 | 2 | 1 | 1 | 1 | 1 | 1 |
| Predictions validated against future outbreak data | |||||||||
| Yes | 24 (41) | 10 | 3 | 4 | 3 | 1 | 1 | 2 | |
| No | 34 (59) | 11 | 10 | 4 | 3 | 4 | 4 | 1 | |
For detailed definitions, see online supplementary material.
*Includes South and Middle America.
†Internet and phone-based system/app/computer programme.
‡Non-categorisable data types.
§Reproduction number (R value).
¶Biological, environmental or economic consequences.
**Or proposed Early Warning System.
CCHF, Crimean-Congo haemorrhagic fever; MERS, Middle East respiratory syndrome; SARS, severe acute respiratory syndrome.