| Literature DB >> 31658267 |
Anna M Stewart-Ibarra1,2,3, Moory Romero1,4, Avery Q J Hinds5, Rachel Lowe6,7,8, Roché Mahon9, Cedric J Van Meerbeeck9, Leslie Rollock10, Marquita Gittens-St Hilaire11,12, Sylvester St Ville13, Sadie J Ryan14,15, Adrian R Trotman9, Mercy J Borbor-Cordova16.
Abstract
BACKGROUND: Small island developing states (SIDS) in the Caribbean region are challenged with managing the health outcomes of a changing climate. Health and climate sectors have partnered to co-develop climate services to improve the management of emerging arboviral diseases such as dengue fever, for example, through the development of climate-driven early warning systems. The objective of this study was to identify health and climate stakeholder perceptions and needs in the Caribbean, with respect to the development of climate services for arboviruses.Entities:
Year: 2019 PMID: 31658267 PMCID: PMC6837543 DOI: 10.1371/journal.pntd.0007772
Source DB: PubMed Journal: PLoS Negl Trop Dis ISSN: 1935-2727
Fig 1Map of the study region.
(A) Location of the Caribbean region within the Americas, (B) Archipelago of islands making up the Caribbean and their location within Meso-America. (C) Location of Dominica (purple) and Barbados (green) within the islands in the region. This map was created using freely available country boundary datafrom GADM.org, rendered in ArcGIS. Image files were created using GIMP freeware.
Arboviral disease cases in Barbados and Dominica.
| Barbados | Dominica | |
|---|---|---|
| Mean annual dengue cases (2012–2016) [ | 2,274 | 169 |
| Mean annual dengue incidence (2012–2016) per 10,000 people [ | 80.0 | 23.5 |
| Total chikungunya cases since 2013 [ | 1,833 suspected | 3,590 suspected |
| Total Zika cases since 2016 [ | 705 suspected | 1,263 suspected |
*Includes suspected and confirmed cases
Demographics of survey and interview participants.
| Responses | Survey | Interview |
|---|---|---|
| Total respondents | 32 | 41 |
| Female | 72% (23) | 56% (23) |
| Male | 28% (9) | 44% (18) |
| Barbados | 63% (20) | 37% (15) |
| Dominica | 31% (10) | 41% (17) |
| Regional | 6% (2) | 15% (6) |
| Health sector | 100% (32) | 76% (31) |
| Climate sector | 24% (10) | |
| 18–30 | 9% (3) | |
| 31–40 | 25% (8) | |
| 41–50 | 31% (10) | |
| 51–65 | 25% (8) | |
| > 65 | 3% (1) | |
| No response | 6% (2) | |
| Associate’s degree | 16% (5) | 0% (0) |
| Bachelor’s degree | 22% (7) | 2% (1) |
| Master’s degree | 59% (19) | 20% (8) |
| MD or PhD degree | 0% (0) | 15% (6) |
| No response | 3% (1) | 61% (25) |
| 1–5 years | 3% (1) | 0% (0) |
| 6–11 years | 13.5% (4) | 2% (1) |
| 12–15 years | 16% (5) | 5% (2) |
| > 15 years | 62.5% (20) | 20% (8) |
| No response | 6% (2) | 76% (31) |
*Data not gathered
**Only individuals from the health sector were surveyed
Perceptions of climate variability impacts on health reported by survey respondents.
Results shown as % (n). This most frequent response per question is highlighted in bold. Adapted from [35–37].
| Questions | No response | Don’t know | Disagree | Neither agree nor disagree | Agree |
|---|---|---|---|---|---|
| My jurisdiction is currently experiencing one or more serious public health problems as a result of climate variability. | 6% (2) | 3% (1) | 13% (4) | 9% (3) | |
| My jurisdiction is currently experiencing an increased risk of diseases transmitted by | 3% (1) | 6% (2) | 3% (1) | 9% (3) | |
| In the next 20 years, my jurisdiction will experience increasing risk of diseases transmitted by | 3% (1) | 13% (4) | 3% (1) | 0 (0) | |
| I am worried about the impact of climate variability on the health and well-being of people in my jurisdiction. | 3% (1) | 0% (0) | 0% (0) | 3% (1) | |
| The effects of climate variability on the health of people in my jurisdiction is an urgent problem. | 3% (1) | 3% (1) | 0% (0) | 13% (4) | |
| There are options/solutions to reduce the effects of climate variability and to improve the health of people in my jurisdiction. | 3% (1) | 3% (1) | 16% (5) | 13% (4) | |
| The people in my jurisdiction are worried about the effects of climate variability on their health and wellbeing. | 6% (2) | 3% (1) | 22% (7) | 13% (4) | |
| My health department currently has ample expertise to assess the potential public health impacts associated with climate variability that could occur in my jurisdiction. | 3% (1) | 0% (0) | 19% (6) | 38% (12) | |
| Dealing with the public health effects of climate variability is an important priority for my health department. | 6% (2) | 0% (0) | 13% (4) | 22% (7) | |
| I am knowledgeable about the potential public health impacts of climate variability. | 3% (1) | 0% (0) | 16% (5) | 3% (1) | |
| The other relevant senior managers in my health department are knowledgeable about the potential public health impacts of climate variability. | 13% (4) | 3% (1) | 19% (6) | 13% (4) | |
| My health department currently has ample expertise to create an effective plan to protect local residents from the health impacts of climate variability. | 6% (2) | 6% (2) | 22% (7) | 31% (10) | |
| My health department currently has sufficient resources to effectively protect local residents from the health impacts of climate variability. | 9% (3) | 6% (2) | 19% (6) | 9% (3) | |
| My health department is able to effectively communicate the health impacts of climate variability to local communities. | 9% (3) | 0% (0) | 31% (10) | 19% (6) |
*Agree and strongly agree were combined into one category, as were disagree and strongly disagree
The relative importance of factors that trigger epidemics of diseases transmitted by Aedes aegypti, as reported by survey respondents.
Results shown as % (n) of survey respondents, ranked by risk factors identified as “very important.” The most frequent responses are marked in bold.
| Categories | No response | Slightly important | Moderately important | Important | Very Important |
|---|---|---|---|---|---|
| Introduction of a new virus to a susceptible population | 0 (0) | 0 (0) | 0 (0) | 9.4 (3) | |
| Water storage behavior | 3.1 (1) | 0 (0) | 0 (0) | 15.6 (5) | |
| Insecticide resistant mosquitoes | 0 (0) | 6.3 (2) | 6.3 (2) | 18.8 (6) | |
| Heavy rainfall | 0 (0) | 3.1 (1) | 6.3 (2) | 43.8 (14) | |
| Human movement | 0 (0) | 3.1 (1) | 6.3 (2) | 43.8 (14) | |
| Insufficient staff/resources for vector control | 0 (0) | 0 (0) | 12.5 (4) | ||
| Lack of community knowledge and awareness | 0 (0) | 3.1 (1) | 15.6 (5) | 37.5 (12) | |
| Limited community engagement/mobilization | 0 (0) | 3.1 (1) | 6.3 (2) | 34.4 (11) | |
| Drought conditions | 3.1 (1) | 31.3 (10) | 9.4 (3) | 25 (8) | |
| High-risk housing conditions | 9.4 (3) | 12.5 (4) | 21.9 (7) | 25 (8) | |
| Low risk perception by communities | 3.1 (1) | 3.1 (1) | 12.5 (4) | 31.3 (10) | |
| Economic barriers to mosquito control by households (e.g., cost of screens or insecticide) | 0 (0) | 9.4 (3) | 31.3 (10) | 25 (8) | |
| El Niño or La Niña events | 3.1 (1) | 6.3 (2) | 18.8 (6) | 21.9 (7) | |
| Warmer air temperatures | 6.3 (2) | 25 (8) | 18.8 (6) | 18.8 (6) |
Fig 2Stakeholder analysis.
Organizations that partner with the health sector (in white) in Barbados and Dominica on issues related to vector control and climate services for health. Organizations in black are current functioning partnerships. Organizations in red are partnerships that need to be strengthened with the health sector.
Fig 3Perceptions of the strengths and weaknesses of the health sector with respect to the capacity to implement an early warning system for arboviral diseases.
EWS = early warning system, GIS = geographic information system, VBDs = vector borne diseases. Results shown as the number of health sector survey respondents (n = 32).