Spatial spillover impact of determinants on child mortality in Pakistan: evidence from Spatial Durbin Model

Sheikh, Muhammad Ramzan; Khan, Sami Ullah; Ahmed, Munir; Ahmad, Rashid; Abbas, Asad; Ullah, Irfan

doi:10.1186/s12889-023-16526-6

Cited by 3 publications

References 83 publications

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Indirect and direct effects of nighttime light on COVID-19 mortality using satellite image mapping approach

Yoneoka,

Eguchi,

Nomura

et al. 2024

Sci Rep

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The COVID-19 pandemic has highlighted the importance of understanding environmental factors in disease transmission. This study aims to explore the spatial association between nighttime light (NTL) from satellite imagery and COVID-19 mortality. It particularly examines how NTL serves as a pragmatic proxy to estimate human interaction in illuminated nocturnal area, thereby impacting viral transmission dynamics to neighboring areas, which is defined as spillover effect. Analyzing 43,199 COVID-19 deaths from national mortality data during January 2020 and October 2022, satellite-derived NTL data, and various environmental and socio-demographic covariates, we employed the Spatial Durbin Error Model to estimate the direct and indirect effect of NTL on COVID-19 mortality. Higher NTL was initially directly linked to increased COVID-19 mortality but this association diminished over time. The spillover effect also changed: during the early 3rd wave (December 2020 – February 2021), a unit (nanoWatts/sr/cm 2 ) increase in NTL led to a 7.9% increase in neighboring area mortality ( p = 0.013). In contrast, in the later 7th wave (July – September 2022), dominated by Omicron, a unit increase in NTL resulted in an 8.9% decrease in mortality in neighboring areas ( p = 0.029). The shift from a positive to a negative spillover effect indicates a change in infection dynamics during the pandemic. The study provided a novel approach to assess nighttime human activity and its influence on disease transmission, offering insights for public health strategies utilizing satellite imagery, particularly when direct data collection is impractical while the collection from space is readily available. Supplementary Information The online version contains supplementary material available at 10.1038/s41598-024-75484-0.

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Indirect and direct effects of nighttime light on COVID-19 mortality using satellite image mapping approach

Yoneoka,

Eguchi,

Nomura

et al. 2024

Sci Rep

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Measuring spatial inequalities in maternal and child mortalities in Pakistan: evidence from geographically weighted regression

Muhammad,

Shahabudin,

Talib

2024

BMC Public Health

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Background In developing countries, the death probability of a child and mother is more significant than in developed countries; these inequalities in health outcomes are unfair. The present study encompasses a spatial analysis of maternal and child mortalities in Pakistan. The study aims to estimate the District Mortality Index (DMI), measure the inequality ratio and slope, and ascertain the spatial impact of numerous factors on DMI scores across Pakistani districts. Method This study used micro-level household datasets from multiple indicator cluster surveys (MICS) to estimate the DMI. To find out how different the DMI scores were, the inequality ratio and slope were used. This study further utilized spatial autocorrelation tests to determine the magnitude and location of the spatial dependence of the clusters with high and low mortality rates. The Geographically Weighted Regression (GWR) model was also applied to examine the spatial impact of socioeconomic, environmental, health, and housing attributes on DMI. Results The inequality ratio for DMI showed that the upper decile districts are 16 times more prone to mortalities than districts in the lower decile, and the districts of Baluchistan depicted extreme spatial heterogeneity in terms of DMI. The findings of the Local Indicator of Spatial Association (LISA) and Moran's test confirmed spatial homogeneity in all mortalities among the districts in Pakistan. The H–H clusters of maternal mortality and DMI were in Baluchistan, and the H–H clusters of child mortality were seen in Punjab. The results of GWR showed that the wealth index quintile has a significant spatial impact on DMI; however, improved sanitation, handwashing practices, and antenatal care adversely influenced DMI scores. Conclusion The findings reveal a significant disparity in DMI and spatial relationships among all mortalities in Pakistan's districts. Additionally, socioeconomic, environmental, health, and housing variables have an impact on DMI. Notably, spatial proximity among individuals who are at risk of death occurs in areas with elevated mortality rates. Policymakers may mitigate these mortalities by focusing on vulnerable zones and implementing measures such as raising public awareness, enhancing healthcare services, and improving access to clean drinking water and sanitation facilities.

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Measuring spatial inequalities in maternal and child mortalities in Pakistan: evidence from geographically weighted regression

Muhammad,

Shahabudin,

Binti

2024

Preprint

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Background In developing countries, the death probability of a child and mother is more significant than in developed countries; these inequalities in health outcomes are unfair. The present study encompasses a spatial analysis of maternal and child mortalities in Pakistan. The study aims to estimate the District Mortality Index (DMI), measure the inequality ratio and slope, and ascertain the spatial impact of various factors on DMI scores across Pakistani districts. Method This study utilized the micro-level household datasets from multiple indicator cluster surveys (MICS) to construct the DMI and used the inequality ratio and slope to measure the disparity in DMI scores. This study further utilized the spatial autocorrelation tests to determine the magnitude and location of the spatial dependence of the clusters with high- and low-mortality rates. The Geographically Weighted Regression (GWR) model was also applied to examine the spatial impact of socioeconomic, environmental, health, and housing attributes on DMI. Results The inequality ratio for DMI showed that the upper decile districts are 16 times more prone to mortalities than districts in the lower decile, and the districts of Baluchistan depicted extreme spatial heterogeneity in terms of DMI. The findings of the Local Indicator of Spatial Association (LISA) and Moran's test confirmed spatial homogeneity in all mortalities among the districts in Pakistan. The H-H clusters of maternal mortality and DMI were located in Baluchistan, and the H-H clusters of child mortality were seen in Punjab. The results of GWR showed that the wealth index quintile has a significant spatial impact on DMI; however, improved sanitation, handwashing practices, and antenatal care adversely influenced DMI scores. Conclusion The findings reveal a significant disparity in DMI and spatial relationships among all mortalities in the districts of Pakistan. Additionally, socioeconomic, environmental, health, and housing variables have an impact on DMI. Notably, spatial proximity among individuals who are at risk of death occurs in areas with elevated mortality rates. Policymakers may mitigate these mortalities by focusing on vulnerable zones and implementing measures such as raising public awareness, enhancing healthcare services, and improving access to clean drinking water and sanitation facilities.

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Spatial spillover impact of determinants on child mortality in Pakistan: evidence from Spatial Durbin Model

Cited by 3 publications

References 83 publications

Indirect and direct effects of nighttime light on COVID-19 mortality using satellite image mapping approach

Indirect and direct effects of nighttime light on COVID-19 mortality using satellite image mapping approach

Measuring spatial inequalities in maternal and child mortalities in Pakistan: evidence from geographically weighted regression

Measuring spatial inequalities in maternal and child mortalities in Pakistan: evidence from geographically weighted regression

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