Disease mapping for informing targeted health interventions: childhood pneumonia in Bohol, Philippines

Geography of Disparity: Connecting COVID-19 Vulnerability and Social Determinants of Health in Colorado

The COVID-19 pandemic has drawn greater attention to social determinants of health and associated health inequities, which disproportionately affect vulnerable populations and places in the U.S. In this study, we explored geographic patterns of local-level COVID-19 vulnerability and associations with social and health determinants across Colorado. To conceptualize social and health determinants and how together they generate risk and exposure, we integrated the concepts of social vulnerability and syndemic to situate COVID-19 vulnerability within a broader hazards of place framework. Using geospatial statistics and GIS, we estimated census tract-level rates of COVID-19, which are not yet available in Colorado, and mapped areas of high and low incidence risk. We also developed composite indices that characterized social and health vulnerabilities to measure multivariate associations with COVID-19 rates. The findings revealed hotspots of persistent risk in mountain communities since the pandemic emerged in Colorado, as well as clusters of risk in the Urban Front Range's central and southern counties, and across many parts of eastern Colorado. Vulnerability analyses indicate that COVID-19 rates were associated with mental health and chronic conditions along with social determinants that represent inequities in education, income, healthcare access, and race/ethnicity (minority percent of population), which may have disproportionately exposed some communities more than others to infection and severe health outcomes. Overall, the findings provide geographic health information about COVID-19 and vulnerability context, which may better inform local decision-making for interventions and policies that support equity of social determinants of health.Supplemental data for this article is available online at https://doi.org/10.1080/08964289.2021.2021382 .

Prevalence of hypoxaemia in children with pneumonia in low-income and middle-income countries: a systematic review and meta-analysis

Background

Pneumonia accounts for around 15% of all deaths of children younger than 5 years globally. Most happen in resource-constrained settings and are potentially preventable. Hypoxaemia is one of the strongest predictors of these deaths. We present an updated estimate of hypoxaemia prevalence among children with pneumonia in low-income and middle-income countries.

Methods

We conducted a systematic review using the following key concepts “children under five years of age” AND “pneumonia” AND “hypoxaemia” AND “low- and middle-income countries” by searching in 11 bibliographic databases and citation indices. We included all articles published between Nov 1, 2008, and Oct 8, 2021, based on observational studies and control arms of randomised and non-randomised controlled trials. We excluded protocol papers, articles reporting hypoxaemia prevalence based on less than 100 pneumonia cases, and articles published before 2008 from the review. Quality appraisal was done with the Joanna Briggs Institute tools. We reported pooled prevalence of hypoxaemia (SpO₂ <90%) by classification of clinical severity and by clinical settings by use of the random-effects meta-analysis models. We combined our estimate of the pooled prevalence of pneumonia with a previously published estimate of the number of children admitted to hospital due to pneumonia annually to calculate the total annual number of children admitted to hospital with hypoxaemic pneumonia.

Findings

We identified 2825 unique records from the databases, of which 57 studies met the eligibility criteria: 26 from Africa, 23 from Asia, five from South America, and four from multiple continents. The prevalence of hypoxaemia was 31% (95% CI 26–36; 101 775 children) among all children with WHO-classified pneumonia, 41% (33–49; 30 483 children) among those with very severe or severe pneumonia, and 8% (3–16; 2395 children) among those with non-severe pneumonia. The prevalence was much higher in studies conducted in emergency and inpatient settings than in studies conducted in outpatient settings. In 2019, we estimated that over 7 million children (95% CI 5–8 million) were admitted to hospital with hypoxaemic pneumonia. The studies included in this systematic review had high τ² (ie, 0·17), indicating a high level of heterogeneity between studies, and a high I² value (ie, 99·6%), indicating that the heterogeneity was not due to chance. This study is registered with PROSPERO, CRD42019126207.

Interpretation

The high prevalence of hypoxaemia among children with severe pneumonia, particularly among children who have been admitted to hospital, emphasises the importance of overall oxygen security within the health systems of low-income and middle-income countries, particularly in the context of the COVID-19 pandemic. Even among children with non-severe pneumonia that is managed in outpatient and community settings, the high prevalence emphasises the importance of rapid identification of hypoxaemia at the first point of contact and referral for appropriate oxygen therapy.

Funding

UK National Institute for Health Research (Global Health Research Unit on Respiratory Health [RESPIRE]; 16/136/109).

Using geo-spatial analysis for assessing the risk of hospital admissions due to community-acquired pneumonia in under-5 children and its association with socially vulnerable areas (Brazil)

Background

The concentration of under-5 child morbidity and mortality due to pneumonia in developing countries reflects the social inequities. This study aimed to map and assess the spatial risk for hospitalization due to Community-Acquired Pneumonia in children under 5 years of age and its association with vulnerable areas.

Methods

Ecological study in the city of Ribeirão Preto, state of São Paulo, Brazil. The study population consisted of hospitalized under-5 children, diagnosed with community-acquired pneumonia, in Ribeirão Preto-São Paulo-Brazil, from 2012 to 2013. Data were collected in different databases, by a trained team, between March 2012 and August 2013 and from the 2010 Demographic Census of the Brazilian Institute of Geography and Statistics. The 956 urban census tracts were considered as the units of analysis. The incidence of cases per 10,000 inhabitants was calculated by census tracts during the study period. For the identification of the spatial risk clusters, the Kernel density estimator and the Getis-Ord Gi* technique were performed. Generalized additive models were used to verify the association between areas with social vulnerability and the occurrence of childhood pneumonia.

Results

The study included 265 children under the age of five, hospitalized due to community-acquired pneumonia. A concentration of cases was identified in the regions with greater social vulnerability (low income, poor housing conditions and homelessness), as well as a lower occurrence of cases in the most developed and economically privileged area of the city. The majority of the children lived in territories served by traditional primary healthcare units, in which the health surveillance and family and community focus are limited. It is important to highlight that the tracts with the highest degrees of vulnerability, such as those identified as high vulnerability (urban) and very high vulnerability (subnormal urban clusters).

Conclusions

The results contribute to the comprehension of the social factors involved in child hospitalization due to pneumonia, based on the analysis of the spatial distribution. This approach revealed a strategic tool for diagnosing the disparities as well presenting evidences for the planning in health and strength health care system in achieving equity, welfare and social protection of children.

Supplementary Information

Supplementary information accompanies this paper at 10.1186/s12887-020-02398-x.

Geographically linked risk factors for enrolment into a fast breathing child pneumonia trial in Lilongwe, Malawi: an Innovative Treatments in Pneumonia (ITIP) secondary analysis

Background

Pneumonia is the leading infectious killer of children less than 5 years of age worldwide. In addition to vaccines that help prevent pneumonia, understanding the environmental and socioeconomic risk factors for child pneumonia is critical to further prevention.

Methods

Data from children with fast breathing pneumonia enrolled in a non-inferiority clinical trial assessing the effectiveness of 3-day placebo versus antibiotic treatment in Lilongwe, Malawi were used to examine environmental and socioeconomic characteristics within the study population. Location of residence was collected for enrolled children, and spatial enrolment rates were compared across Lilongwe using a spatial scan statistic.

Results

Data from 1101 children were analysed. Three urban subdistricts (locally known as ‘Areas’) (Areas 24, 36 and 38) out of 51 were identified with higher than expected enrolment. These three areas were associated with higher rates of poverty (37.8% vs 23.9%) as well as informal settlements and poorer sanitation (42.4% vs 7.4%) than other areas. Parents of enrolled children from these areas also had lower rates of secondary education compared with parents of children enrolled from other areas (55% vs 67% (p<0.01) among fathers; 47% vs 54% (p<0.01) among mothers).

Conclusion

In Lilongwe, areas with higher rates of poverty, informal settlements and poor sanitation contributed higher than expected enrolment of children to our fast breathing child pneumonia clinical trial when compared with other areas. Additional research is needed to evaluate the impact of environmental and socioeconomic risk factors, along with vaccination status, on the incidence of fast breathing pneumonia in children living in this region.

Distance to health services modifies the effect of an 11-valent pneumococcal vaccine on pneumonia risk among children less than 2 years of age in Bohol, Philippines

Background

Both vaccine trials and surveillance studies typically use passive surveillance systems to monitor study outcomes, which may lead to under-reporting of study outcomes in areas with poor access to care. This detection bias can have an adverse effect on conventional estimates of pneumonia risk derived from vaccine trials.

Methods

We conducted a secondary analysis of a randomized, placebo-controlled, double-blind vaccine trial that examined the efficacy of an 11-valent pneumococcal vaccine (PCV) among children less than 2 years of age in Bohol, Philippines. Trial data were linked to the residential location of each participant using a geographical information system. The study was conducted using 11 729 children who received three doses of any study vaccine (PCV11) or placebo. Multivariate Cox proportional hazards models were used to examine major risk factors for pneumonia diagnosis and the relationship between distance to Bohol Regional Hospital (BRH) and vaccination with PCV with risk for pneumonia diagnosis.

Results

There was a significant interaction effect between distance from BRH and vaccination with PCV11 on pneumonia risk. Among children living 12 km from BRH, vaccination with PCV11 was associated with a decreased hazard ratio for radiographic pneumonia, compared with vaccination with the study placebo [0.57, 95% confidence interval (CI) 0.37-0.86). However, for children living 1 km from BRH, there was little difference in risk of radiographic pneumonia diagnosis between children vaccinated with PCV11 and those given the study placebo.

Conclusion

Children living close to BRH had no documented reduction in the primary study outcome from PCV11, whereas those at greater distance experienced a substantial reduction. Because of detection bias caused by distance to BRH, in spatial analysis of vaccine trial results it may be necessary to adjust estimates of pneumonia risk and vaccine efficacy. Failure to consider the geographical dimension of trials may lead to underestimates of efficacy which might influence public health planning efforts.

Using Spatial Analysis to Inform Community Immunization Strategies

INTRODUCTION

Recent pertussis outbreaks in the United States suggest our response to local disease outbreaks (eg, vaccine-preventable Bordetella pertussis) may benefit from understanding and applying spatial analytical methods that use data from immunization information systems at a subcounty level.

METHODS

A 2012 study on Denver, CO, residents less than 19 years of age confirmed pertussis cases and immunization information system records were geocoded and aggregated to the census tract (CT) level. An algorithm assessed whether individuals were up-to-date (UTD) for pertussis vaccines. Pearson, Spearman, and Kendall correlations assessed relations between disease incidence and pertussis vaccine coverage. Using spatial analysis software, disease incidence and UTD rates were spatially weighted, and smoothed. Global and local autocorrelations based on univariate Moran's I spatial autocorrelation statistics evaluated whether a CT's rate belong to a cluster based on incidence or UTD measures.

RESULTS

Overall disease incidence rate was 116.8/100 000. Assessment of pertussis vaccination coverage was available for 90% of the population. Among 134 672 Denver residents less than 19 years old, 103 496 (77%) were UTD for pertussis vaccines. Raw correlation coefficients showed weak relationships between incidence and immunization rates due to the presence of outliers. With geospatial and clustering analysis, estimates and correlation coefficients were improved with statistically significant Moran's I values for global and local autocorrelations rejecting the null hypothesis that incidence or UTD rates were randomly distributed. With evidence indicating the presence of clusters, smoothed and weighted disease incidence and UTD rates in 144 CTs identified 21 CTs (15%) for potential public health intervention.

CONCLUSIONS

Correlation of raw disease incidence and vaccine UTD rates in subcounty regions showed limited association, providing limited information for decision making. By assessing for clusters using spatial analysis methods, we identified CTs with higher incidence and lower immunization coverage for targeted public health interventions.