This document summarizes climate forecasting and its applications to predicting health risks. It discusses seasonal forecasts from ECMWF of summer temperature and rainfall. It shows areas with medium forecast skill for dry and warm conditions in summer. It also discusses operational El Niño forecasts up to 29 months in advance and their application to dengue prediction. Further, it outlines mechanistic models of malaria in Senegal and cholera in Bangladesh, as well as dengue forecasts for the 2014 World Cup. Finally, it mentions a platform for COVID-19 prediction and the ArboCat website for information on arboviruses.

1. Xavier Rodó, ICREA
Climate & Health Program
Integración de la información climática
para la previsión de riesgos
‘El día después...’

2. Climate Services

3. Global Seasonal Forecasts (ECMWF)
summer (JAS) temperature
summer (JAS) rainfall
1-3 meses
Summer
Temperature
Summer
Precipitation
Regional

4. A QGIS project to interactively overlap skill contours for different variables, seasons and terciles.
The forecast system is ECMWF System4 with 15 ens. members.
The example above shows areas with medium skill (ROCSS > 0.2) for dry (blue contour) and warm (red contour)
conditions for the boreal summer (JJA). The forecasts started 1 month before the season.
Interesting hotspots: Central America-Caribbean, northern coast of Guinea gulf, Cambodia-Vietnam, Indonesia-
Philippines, Horn of Africa…
IC3 Climate Skill Finder
Garcia et al., in prep
Skill finder and the geography of ‘predictable’ diseases

5.  Warm El Niño events cause major
disasters and economic burden in many
parts of the world.
 Operational forecasts at a few years lead
time could save lives and resources, but
are still a major challenge for the climate
community.
 Our model has successfully hind casted
such events at leads of up to 29 months.
 Application to predicting dengue (Brazil,
Ecuador, Puerto Rico and Thailand)
Prediction of El Niño-Southern Oscillation events

6. Modelling Infectious Diseases

7. Malaria (endemic vs epidemic areas)
Senegal: The ‘perfect’ VBD case (for climate/immunity)
5Km

8. SDE using MIF
(Including Population change, rainfall/T and drug
treatment)
Dielmo
Ndiop
Ethiopia
Senegal
Moçambiq
Kenya
Malaria (Senegal)
CLIMATE

9. 0
4
8
12
1995 1998 2001 2004 2007 2010 2013 2016
Time
Choleracasesper10000
A Mechanistic temporal model
0
2
4
1995 1998 2001 2004 2007 2010 2013 2016
Time
Avg.choleracasesper10000
B Statistical spatio-temporal model
Training Hindcast Forecast
Observed data 1995-2015
2016 Cholera forecast for Dhaka...
Large outbreak!

10. DENGUE
BBC News: http://www.bbc.com/news/health-27441789
Dengue forecast for a major global event: The 2014 soccer World Cup
Microregion Warning Probability
p(low, medium,
high)
Skill
score
(RPSS)
Belo Horizonte Medium p(65%, 24%, 11%) 0·14
Brasília Low p(73%, 20%, 7%) 0·14
Cuiabá Low p(71%, 22%, 7%) 0·01
Curitiba Low p(100%, 0%, 0%) 1
Fortaleza High p(34%, 20%, 46%) 0·5
Manaus Medium p(63%, 25%, 12%) 0·15
Natal High p(32%, 20%, 48%) 0·67
Porto Alegre Low p(100%, 0%, 0%) 1
Recife High p(57%, 24%, 19%) 0·23
Salvador Medium p(56%, 27%, 17%) 0·14
São Paulo Low p(99%, 1%, 0%) 0·99
Rio de Janeiro Medium p(62%, 25%, 13%) 0·21
1.Hit 2.False
hit rate: 57% (33%)
false alarm rate (type I error rate): 23% (13%)
miss rate (type II error rate): 43% (67%)

11. Contact networks
Chikungunya in the Caribbean
2014

12. COVID-19 Prediction Platform
Tau
Bangladesh Brazil Kenya
Italy
I I I
RRR
DDD

13. www.arbocat.org