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Health Portugal

Vulnerabilities - Heat stress

Heat waves combined with urban heat islands (9) can result in large death tolls with the elderly, the unwell, the socially isolated, and outdoor workers (10) being especially vulnerable. Heat waves thus pose a future challenge for major cities (11).

In continental Portugal, the highest frequency of heat waves was recorded in the 1990s, with particularly long and widespread events in 1981, 1991, 2003 and, more recently, two heat waves between the end of May and June 2005 (1). 

From an environmental and health perspective, it was the relatively short-lived heat wave that occurred during the first fortnight of August 2003 that had a major impact in Europe. In Portugal, an estimate of the excess mortality for the 1st fortnight of August 2003 was about 2000 people, mostly above 75 years old (2). For the whole of summer 2003, the number of heat related deaths in Western Europe is believed to amount to over 44,000 (5,8).

The annual heat-related death rates in Lisbon may increase from between 5.4 and 6 per 100,000 in 1980–1998 to between 8.5 and 12.1 by the 2020s and to a maximum of 29.5 by the 2050s, if no adaptation occurs. Other studies project an increase to between 5.8 and 15.1 for the 2020s, and 7.3 to 35.6 by the 2050s (4). The projected warmer and more variable weather may result in better dispersion of nitrogen dioxide levels in winter, whereas the higher temperatures may reduce air quality during the warmer months by increasing tropospheric ozone levels (3).

The experience of 2003 shows that those most likely to die of the heat are the old, the chronically ill, and the isolated. Both northern and southern Europe are at risk (8).

Urban heat island Lisbon

The urban heat island effect in Lisbon is mainly a nighttime phenomenon (24). The annual-mean urban heat island effect over Lisbon in the period 1971 – 2005 was found to be positive during nighttime (+3 °C, city warmer than rural), with a maximum during winter (+4 °C) and a minimum during summer (+2 °C). During daytime, the annual-mean urban heat island effect was found to be slightly negative, with an annual-mean < −1 °C (city cooler than rural). During daytime this effect changed signal between +1 °C during winter and −1 °C during summer (22). These results are consistent with previous studies reporting a negative daytime urban heat island effect over relatively dry regions, where urban surfaces are characterized by lower surface albedo and higher surface roughness compared to the rural surroundings (23). 

The urban heat island effect in Lisbon is mainly a nighttime phenomenon. More recent data, over the period 2008-2014, showed a heat island effect in Lisbon varying between close to 0°C on a rainy day to about 1,5°C on a sunny winter day (24).

Vulnerabilities - Tick-borne diseases

Higher temperatures may increase the transmission risk of zoonoses that are currently endemic to Portugal, such as leishmaniasis, Lyme disease, and Mediterranean spotted fever (3).

Vulnerabilities - Mosquito-borne diseases

While climatic factors may favor autochthonous transmission, increased vector density, and accelerated parasite development, other factors (socioeconomic, building codes, land use, treatment, etc) limit the likelihood of climate related re-emergence of malaria in Europe (6).

Vulnerabilities - Sand-fly-borne diseases

Leishmaniasis is a protozoan parasitic infection caused by Leishmania infantum that is transmitted to human beings through the bite of an infected female sandfly. Sandfly distribution in Europe is south of latitude 45⁰N and less than 800 m above sea level, although it has recently expanded as high as 49⁰N. Currently, sandfly vectors have a substantially wider range than that of L infantum, and imported cases of infected dogs are common in central and northern Europe. Once conditions make transmission suitable in northern latitudes, these imported cases could act as plentiful source of infections, permitting the development of new endemic foci. Conversely, if climatic conditions become too hot and dry for vector survival, the disease may disappear in southern latitudes. Thus, complex climatic and environmental changes (such as land use) will continue to shift the dispersal of leishmaniasis in Europe (6).

Vulnerabilities - Floods

Floods are the most common natural disaster in Europe. The adverse human health consequences of flooding are complex and far-reaching: these include drowning, injuries, and an increased incidence of common mental disorders. Anxiety and depression may last for months and possibly even years after the flood event and so the true health burden is rarely appreciated (7).

Effects of floods on communicable diseases appear relatively infrequent in Europe. The vulnerability of a person or group is defined in terms of their capacity to anticipate, cope with, resist and recover from the impact of a natural hazard. Determining vulnerability is a major challenge. Vulnerable groups within communities to the health impacts of flooding are the elderly, disabled, children, women, ethnic minorities, and those on low incomes (7).

Adaptation strategies - Portugal

In Portugal an operational Heat Health Warning System has existed since the summer of 1999. This system is based on meteorological data and gives three days advanced heat wave predictions. In 2003, the surveillance partners had difficulties in conveying out messages to the population, using the media, late in the heat stress period. From the 2003 summer experience is was concluded that active ways must be sought to convey information to the population, when such a silent disaster is predicted. Passive systems, such as using the media to spread messages of interest during heat stress periods, are not reliable especially in a very long heat wave (3).

In 2004, a contingency plan has been approved for heat waves in order to be able react to situations similar to those of 2003. The aim is to minimize the effects of high temperatures on health through a warning and adequate response system, to define guidelines for intervention and to strengthen the cross-institutional coordination. The considers four warning levels: Level 1 – Blue warning – surveillance; Level 2 – Yellow warning – effects on health foreseen; Level 3 – Orange warning - heat wave – severe consequences foreseen relating to health and mortality; Level 4 – Red warning - acute heat wave – very severe consequences foreseen relating to health and mortality (1).

Adaptation strategies - General - Heatwaves

The outcomes from the two European heat waves of 2003 and 2006 have been summarized by the IPCC (12) and are summarized below. They include public health approaches to reducing exposure, assessing heat mortality, communication and education, and adapting the urban infrastructure.

1. Public health approaches to reducing exposure

A common public health approach to reducing exposure is the Heat Warning System (HWS) or Heat Action Response System. The four components of the latter include an alert protocol, community response plan, communication plan, and evaluation plan (13). The HWS is represented by the multiple dimensions of the EuroHeat plan, such as a lead agency to coordinate the alert, an alert system, an information outreach plan, long-term infrastructural planning, and preparedness actions for the health care system (14).

The European Network of Meteorological Services has created Meteoalarm as a way to coordinate warnings and to differentiate them across regions (15). There are a range of approaches used to trigger alerts and a range of response measures implemented once an alert has been triggered. In some cases, departments of emergency management lead the endeavor, while in others public health-related agencies are most responsible (16).

2. Assessing heat mortality

Assessing excess mortality is the most widely used means of assessing the health impact of heat-related extreme events.

3. Communication and education

One particularly difficult aspect of heat preparedness is communicating risk. In many locations populations are unaware of their risk and heat wave warning systems go largely unheeded (17). Some evidence has even shown that top-down educational messages do not result in appropriate resultant actions (18).

More generally, research shows that communication about heat preparedness centered on engaging with communities results in increased awareness compared with top-down messages (19).

4. Adapting the urban infrastructure

Several types of infrastructural measures can be taken to prevent negative outcomes of heat-related extreme events. Models suggest that significant reductions in heat-related illness would result from land use modifications that increase albedo, proportion of vegetative cover, thermal conductivity, and emissivity in urban areas (20). Reducing energy consumption in buildings can improve resilience, since localized systems are less dependent on vulnerable energy infrastructure. In addition, by better insulating residential dwellings, people would suffer less effect from heat hazards. Financial incentives have been tested in some countries as a means to increase energy efficiency by supporting those who are insulating their homes. Urban greening can also reduce temperatures, protecting local populations and reducing energy demands (21).


The references below are cited in full in a separate map 'References'. Please click here if you are looking for the full references for Portugal.

  1. Portuguese Environment Agency with the cooperation of Ecoprogresso – Environment and Development Consultants, SA (2006)
  2. Pereira et al. (2005)
  3. Casimiro et al. (2006)
  4. Dessai (2003)
  5. Swedish Government Official Reports (2007)
  6. Semenza and Menne (2009)
  7. Hajat et al. (2003)
  8. Kosatsky (2005)
  9. Basara et al. (2010); Tan et al. (2010), in: IPCC (2012)
  10. Maloney and Forbes (2011), in: IPCC (2012)
  11. Endlicher et al. (2008); Bacciniet al. (2011), both in: IPCC (2012)
  12. IPCC (2012)
  13. Health Canada (2010), in: IPCC (2012)
  14. WHO (2007), in: IPCC (2012)
  15. Bartzokas et al. (2010), in: IPCC (2012)
  16. McCormick (2010b), in: IPCC (2012)
  17. Luber and McGeehin (2008), in: IPCC (2012)
  18. Semenza et al. (2008)), in: IPCC (2012)
  19. Smoyer-Tomic and Rainham (2001), in: IPCC (2012)
  20. Yip et al. (2008); Silva et al. (2010), both in: IPCC (2012)
  21. Akbari et al. (2001), in: IPCC (2012)
  22. Nogueira et al. (2020)
  23. Zhao et al. (2014); Shastri et al. (2017); Krayenhoff et al. (2018); Manoli et al. (2019), all in: Nogueira et al. (2020)
  24. Reis et al. (2022)