TY - JOUR
T1 - Cross-border malaria drivers and risk factors on the Brazil-Venezuela border between 2016 and 2018
AU - Wangdi, Kinley
AU - Wetzler, Erica
AU - Marchesini, Paola
AU - Villegas, Leopoldo
AU - Canavati, Sara
N1 - Funding Information:
This study was supported by World Vision US, Global Development One, USA, and Asociacion Civil Impacto Social (ASOCIS), Venezuela.
Funding Information:
Authors would like to thank the Ministries of Health of Brazil and Venezuela for sharing the data, and all of the health workers in Roraima and Bolivar for their contributions to collecting and reporting the data. We would also like to thank Jorge Moreno (Centro de Investigación de Campo Francesco Vitanza, Tumeremo, Bolívar, Venezuela) and Maria Villegas (Global Development One, Silver Spring, Maryland, USA) who supported data acquisition and entry for the data from Bolivar state.
Publisher Copyright:
© 2022, The Author(s).
PY - 2022/12
Y1 - 2022/12
N2 - Globally, cross-border importation of malaria has become a challenge to malaria elimination. The border areas between Brazil and Venezuela have experienced high numbers of imported cases due to increased population movement and migration out of Venezuela. This study aimed to identify risk factors for imported malaria and delineate imported malaria hotspots in Roraima, Brazil and Bolivar, Venezuela between 2016 and 2018. Data on malaria surveillance cases from Roraima, Brazil and Bolivar, Venezuela from 2016 to 2018 were obtained from national surveillance systems: the Brazilian Malaria Epidemiology Surveillance Information System (SIVEP-Malaria), the Venezuelan Ministry of Health and other non-government organizations. A multivariable logistic regression model was used to identify the risk factors for imported malaria. Spatial autocorrelation in malaria incidence was explored using Getis-Ord (Gi*) statistics. During the study period, there were 11,270 (24.3%) and 4072 (0.7%) imported malaria cases in Roraima, Brazil and Bolivar, Venezuela, respectively. In the multivariable logistic regression for Roraima, men were 28% less likely to be an imported case compared to women (Adjusted Odds Ratio [AOR] = 0.72; 95% confidence interval [CI] 0.665, 0.781). Ages 20-29 and 30-39 were 90% (AOR = 1.90; 95% CI 1.649, 2.181) and 54% (AOR = 1.54; 95% CI 1.331, 1.782) more likely to be an imported case compared to the 0-9 year age group, respectively. Imported cases were 197 times (AOR = 197.03; 95% CI 175.094, 221.712) more likely to occur in miners than those working in agriculture and domestic work. In Bolivar, cases aged 10-19 (AOR = 1.75; 95% CI 1.389, 2.192), 20-29 (AOR = 2.48; 95% CI 1.957, 3.144), and 30-39 (AOR = 2.29; 95% CI 1.803, 2.913) were at higher risk of being an imported case than those in the 0-9 year old group, with older age groups having a slightly higher risk compared to Roraima. Compared to agriculture and domestic workers, tourism, timber and fishing workers (AOR = 6.38; 95% CI 4.393, 9.254) and miners (AOR = 7.03; 95% CI 4.903, 10.092) were between six and seven times more likely to be an imported case. Spatial analysis showed the risk was higher along the international border in the municipalities of Roraima, Brazil. To achieve malaria elimination, cross-border populations in the hotspot municipalities will need targeted intervention strategies tailored to occupation, age and mobility status. Furthermore, all stakeholders, including implementers, policymakers, and donors, should support and explore the introduction of novel approaches to address these hard-to-reach populations with the most cost-effective interventions.
AB - Globally, cross-border importation of malaria has become a challenge to malaria elimination. The border areas between Brazil and Venezuela have experienced high numbers of imported cases due to increased population movement and migration out of Venezuela. This study aimed to identify risk factors for imported malaria and delineate imported malaria hotspots in Roraima, Brazil and Bolivar, Venezuela between 2016 and 2018. Data on malaria surveillance cases from Roraima, Brazil and Bolivar, Venezuela from 2016 to 2018 were obtained from national surveillance systems: the Brazilian Malaria Epidemiology Surveillance Information System (SIVEP-Malaria), the Venezuelan Ministry of Health and other non-government organizations. A multivariable logistic regression model was used to identify the risk factors for imported malaria. Spatial autocorrelation in malaria incidence was explored using Getis-Ord (Gi*) statistics. During the study period, there were 11,270 (24.3%) and 4072 (0.7%) imported malaria cases in Roraima, Brazil and Bolivar, Venezuela, respectively. In the multivariable logistic regression for Roraima, men were 28% less likely to be an imported case compared to women (Adjusted Odds Ratio [AOR] = 0.72; 95% confidence interval [CI] 0.665, 0.781). Ages 20-29 and 30-39 were 90% (AOR = 1.90; 95% CI 1.649, 2.181) and 54% (AOR = 1.54; 95% CI 1.331, 1.782) more likely to be an imported case compared to the 0-9 year age group, respectively. Imported cases were 197 times (AOR = 197.03; 95% CI 175.094, 221.712) more likely to occur in miners than those working in agriculture and domestic work. In Bolivar, cases aged 10-19 (AOR = 1.75; 95% CI 1.389, 2.192), 20-29 (AOR = 2.48; 95% CI 1.957, 3.144), and 30-39 (AOR = 2.29; 95% CI 1.803, 2.913) were at higher risk of being an imported case than those in the 0-9 year old group, with older age groups having a slightly higher risk compared to Roraima. Compared to agriculture and domestic workers, tourism, timber and fishing workers (AOR = 6.38; 95% CI 4.393, 9.254) and miners (AOR = 7.03; 95% CI 4.903, 10.092) were between six and seven times more likely to be an imported case. Spatial analysis showed the risk was higher along the international border in the municipalities of Roraima, Brazil. To achieve malaria elimination, cross-border populations in the hotspot municipalities will need targeted intervention strategies tailored to occupation, age and mobility status. Furthermore, all stakeholders, including implementers, policymakers, and donors, should support and explore the introduction of novel approaches to address these hard-to-reach populations with the most cost-effective interventions.
KW - Aged
KW - Brazil/epidemiology
KW - Child
KW - Child, Preschool
KW - Female
KW - Humans
KW - Incidence
KW - Infant
KW - Infant, Newborn
KW - Malaria/epidemiology
KW - Male
KW - Risk Factors
KW - Venezuela/epidemiology
UR - http://www.scopus.com/inward/record.url?scp=85128103753&partnerID=8YFLogxK
U2 - 10.1038/s41598-022-09819-0
DO - 10.1038/s41598-022-09819-0
M3 - Article
C2 - 35411064
SN - 2045-2322
VL - 12
SP - 1
EP - 13
JO - Scientific Reports
JF - Scientific Reports
IS - 1
M1 - 6058
ER -