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1.
Emerg Infect Dis ; 29(8): 1524-1530, 2023 08.
Article in English | MEDLINE | ID: mdl-37486156

ABSTRACT

Guatemala implemented wastewater-based poliovirus surveillance in 2018, and three genetically unrelated vaccine-derived polioviruses (VDPVs) were detected in 2019. The Ministry of Health (MoH) response included event investigation through institutional and community retrospective case searches for acute flaccid paralysis (AFP) during 2018-2020 and a bivalent oral polio/measles, mumps, and rubella vaccination campaign in September 2019. This response was reviewed by an international expert team in July 2021. During the campaign, 93% of children 6 months <7 years of age received a polio-containing vaccine dose. No AFP cases were detected in the community search; institutional retrospective searches found 37% of unreported AFP cases in 2018‒2020. No additional VDPV was isolated from wastewater. No evidence of circulating VDPV was found; the 3 isolated VDPVs were classified as ambiguous VDPVs by the international team of experts. These detections highlight risk for poliomyelitis reemergence in countries with low polio vaccine coverage.


Subject(s)
Poliomyelitis , Poliovirus , Child , Humans , Poliovirus Vaccine, Oral/adverse effects , Wastewater , Guatemala/epidemiology , Retrospective Studies , Poliomyelitis/epidemiology , Poliomyelitis/prevention & control , Environmental Monitoring
2.
Am J Clin Nutr ; 112(Suppl 2): 816S-829S, 2020 09 14.
Article in English | MEDLINE | ID: mdl-32860403

ABSTRACT

BACKGROUND: Peru reduced its under-5 child stunting prevalence notably from 31.3% in 2000 to 13.1% in 2016. OBJECTIVES: We aimed to study factors and key enablers of child stunting reduction in Peru from 2000-2016. METHODS: Demographic and Health Surveys were used to conduct descriptive analyses [height-for-age z scores (HAZ) means and distributions, equity analysis, predicted child growth curves through polynomial regressions] and advanced regression analyses. An ecological (at department level) multilevel regression analysis was conducted to identify the major predictors of stunting decline from 2000 to 2016, and Oaxaca-Blinder decomposition was conducted to identify the relative contribution of each factor to child HAZ change. A systematic literature review, policy and program analysis, and interviews with relevant stakeholders were conducted to understand key drivers of stunting decline in Peru. RESULTS: The distribution of HAZ scores showed a slight rightward shift from 2000 to 2007/2008, and a greater shift from 2007/2008 to 2016. Stunting reduction was higher in the lowest wealth quintile, in rural areas, and among children with the least educated mothers. Decomposing predicted changes showed that the most important factors were increased maternal BMI and maternal height, improved maternal and newborn health care, increased parental education, migration to urban areas, and reduced fertility. Key drivers included the advocacy role of civil society and political leadership around poverty and stunting reduction since the early 2000s. Key enablers included the economic growth and the consolidation of democracy since the early 2000s, and the acknowledgement that stunting reduction needs much more than food supplementation. CONCLUSIONS: Peru reduced child stunting owing to improved socioeconomic determinants, sustained implementation of out-of-health-sector and within-health-sector changes, and implementation of health interventions. These efforts were driven through a multisectoral approach, strong civil society advocacy, and keen political leadership. Peru's experience offers useful lessons on how to tackle the problem of stunting under differing scenarios, with the participation of multiple sectors.


Subject(s)
Growth Disorders/epidemiology , Child Development , Child, Preschool , Educational Status , Female , Growth Disorders/economics , Growth Disorders/physiopathology , Growth Disorders/prevention & control , Humans , Infant , Male , Peru/epidemiology , Poverty , Prevalence , Rural Population/statistics & numerical data , Socioeconomic Factors , Urban Population/statistics & numerical data
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