Table 1

Principal findings of outbreak prediction articles, by disease

All diseasesRift Valley feverZika diseaseCCHFEbola and Marburg diseaseLassa feverMERSNipah and Henipa virusSARS
Number of articles (%)58 (100)21 (36)13 (22)8 (14)6 (10)5 (9)4 (7)2 (3)2 (3)
Date range
 2010–201947 (81)151365442
 2000–20099 (16)42112
 1990–19992 (3)2
Region of study
 African continent28 (48)18165
 Asia-Pacific4 (7)31
 Europe3 (5)1111
 Middle East9 (16)261
 North America2 (3)11
 Latin America and Caribbean*5 (9)5
 Global8 (14)1322
Prediction methodology
 Risk mapping26 (45)14613211
 Regression model21 (36)754311
 Time series forecasting23 (40)954212
 Qualitative7 (12)42211
 Other quantitative9 (16)12112112
 Species niche model15 (26)341531
 Machine learning16 (28)362221
 Spatiotemporal model25 (43)134422
 Internet/phone/computer†6 (10)51
 Early warning system**17 (29)75311
 Incidence modelling11 (19)551
Model type
 Deterministic6 (10)21111
 Stochastic35 (60)11963321
 Mixed6 (10)111212
 Not applicable/not stated11 (19)72111
Data sources
 Case data47 (81)1212765322
 Other patient health data13 (22)
 Meteorological/climate39 (67)1975431
 Vector/host31 (53)1374531
 Sociodemographic24 (41)77332211
 Behaviour (way of infection)8 (14)211121
 Healthcare5 (9)121111
 Transportation12 (21)2412212
 Internet†7 (12)151
 Geographical32 (55)151365442
 Economic9 (16)241121
 Ecological18 (31)93242
 Expert opinion5 (9)411
 Other‡6 (10)11132
Prediction outcome
 Future cases21 (36)195132
 Outbreak risk factors37 (64)1947631
 Immunity parameters§7 (12)21112
 Risk maps29 (50)42112
 Spatial prediction44 (76)1910544112
 Temporal prediction39 (67)157642311
 Outbreak risk36 (62)149353221
 Spillover events6 (10)2232
 Bio-Env-Econ consequences¶4 (7)311
 Env transmission suitability20 (34)1042421
 Population at risk8 (14)3223
 Introduction risk5 (9)122111
 Effect of climate change3 (5)2
 Epidemic dynamics17 (29)3442121
Implementation of prediction/methods by decision makers
 Yes6 (10)411
 Suggested30 (52)104644311
 No22 (38)78211111
Predictions validated against future outbreak data
 Yes24 (41)10343112
 No34 (59)111043441
  • 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.