Editing IPCC:AR6/WGII/Chapter-12 (section)

==== 12.5.6.5 Challenges and Opportunities ====

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Despite the proliferation of disaster EWSs in the region, only 37 can be considered operational, because many of these systems do not operate or function properly or do not meet the requirements that would allow them to be considered EWSs ( [[#UNESCO--2012|UNESCO, 2012]] ). Sustainable financing and political support are needed to ensure the functioning of disaster EWSs ( ''high confidence'' ) (Table 12.11). Several studies identified difficulties in implementing disaster EWSs due to a lack of community engagement and response to the alerts that are issued ( [[#del%20Granado--2016|del Granado et al., 2016]] ; [[#López-García--2017|López-García et al., 2017]] ). To address these challenges, the document ‘Developing Early Warning Systems: A Checklist’ provides guidance for the implementation of a ''people-centred approach to early warning systems'' , as proposed in the Hyogo Framework for Action 2005–2015 ( [[#Wiltshire--2006|Wiltshire, 2006]] ).

With respect to the development of climate-driven epidemic forecasts, efforts are needed to improve the utility of such forecasts for the health sector. Few such forecasts have been operationalised to inform health-sector decision-making. A review of 73 studies that predicted and forecasted Zika virus infections (42% from the Americas) identified a high degree of variation in access, reproducibility, timeliness and incorporation of uncertainty ( [[#Kobres--2019|Kobres et al., 2019]] ). A recent systematic review of epidemic forecasting and prediction studies found that no reporting guidelines exist; the development of guidance to improve the transparency, quality and implementation of forecast models in the public health sector was recommended ( [[#Pollett--2020|Pollett et al., 2020]] ). An earlier review of dengue early-warning models found that few models incorporated both spatial and temporal aspects of disease risk ( [[#Racloz--2012|Racloz et al., 2012]] ), limiting their potential application as an adaptation strategy by the health sector. Advances have been made in the last decade with respect to modelling and computing tools, increasing access to digital climate information and health records and the use of Earth observations to forecast climate-sensitive diseases ( [[#Fletcher--2021|Fletcher et al., 2021]] ; [[#Wimberly--2021|Wimberly et al., 2021]] ).

The growing field of implementation science—defined as ‘a discipline focused on systematically examining the gap between knowledge and action’—represents another opportunity to address the challenges and barriers to using climate information for health-sector decision-making ( [[#Boyer--2020|Boyer et al., 2020]] ). Implementation science in the health sector in CSA is nascent; research in this area could help to address barriers to mainstreaming climate information in the health sector as an adaptation strategy (Table 12.11; Table SM12.7).

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