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Finding the gap: revealing local disparities in coverage of maternal, newborn and child health services in South Sudan using lot quality assurance sampling.
Trop Med Int Health. 2015 Dec; 20(12):1711-21.TM

Abstract

OBJECTIVES

We adapted a rapid monitoring method to South Sudan, a new nation with one of the world's highest maternal and child mortality rates, aiming to assess coverage of maternal, neonatal and child health (MNCH) services at the time of independence, and introducing a monitoring and evaluation system (M&E) for equity-sensitive tracking of progress related to Millennium Development Goals (MDG) 4 and 5 at national, state and county levels to detect local variability.

METHODS

We conducted a national cross-sectional household survey among women from six client populations in all, but six of South Sudan's 79 counties. We used lot quality assurance sampling (LQAS) to measure coverage with diverse MNCH indicators to obtain information for national-, state- and county-level health system management decision-making.

RESULTS

National coverage of MNCH services was low for all maternal and neonatal care, child immunisation, and child care indicators. However, results varied across states and counties. Central Equatoria State (CES), where the capital is located, showed the highest coverage for most indicators (e.g. ≥4 antenatal care visits range: 4.5% in Jonglei to 40.1% in CES). Urban counties often outperformed rural ones.

CONCLUSIONS

This adaptation of LQAS to South Sudan demonstrates how it can be used in the future as an M&E system to track progress of MDGs at national, state and county levels to detect local disparities. Overall, our data reveal a desperate need for improving MNCH service coverage in all states.

Authors+Show Affiliations

Liverpool School of Tropical Medicine, International Public Health Department, Liverpool, UK.Liverpool School of Tropical Medicine, International Public Health Department, Liverpool, UK.Ministry of Health of the Republic of South Sudan, Directorate of Policy, Planning, Budgeting and Research, Juba, South Sudan.Liverpool School of Tropical Medicine, International Public Health Department, Liverpool, UK.Liverpool School of Tropical Medicine, International Public Health Department, Liverpool, UK.Liverpool School of Tropical Medicine, International Public Health Department, Liverpool, UK.

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

26432978

Citation

Valadez, Joseph J., et al. "Finding the Gap: Revealing Local Disparities in Coverage of Maternal, Newborn and Child Health Services in South Sudan Using Lot Quality Assurance Sampling." Tropical Medicine & International Health : TM & IH, vol. 20, no. 12, 2015, pp. 1711-21.
Valadez JJ, Berendes S, Lako R, et al. Finding the gap: revealing local disparities in coverage of maternal, newborn and child health services in South Sudan using lot quality assurance sampling. Trop Med Int Health. 2015;20(12):1711-21.
Valadez, J. J., Berendes, S., Lako, R., Gould, S., Vargas, W., & Milner, S. (2015). Finding the gap: revealing local disparities in coverage of maternal, newborn and child health services in South Sudan using lot quality assurance sampling. Tropical Medicine & International Health : TM & IH, 20(12), 1711-21. https://doi.org/10.1111/tmi.12613
Valadez JJ, et al. Finding the Gap: Revealing Local Disparities in Coverage of Maternal, Newborn and Child Health Services in South Sudan Using Lot Quality Assurance Sampling. Trop Med Int Health. 2015;20(12):1711-21. PubMed PMID: 26432978.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Finding the gap: revealing local disparities in coverage of maternal, newborn and child health services in South Sudan using lot quality assurance sampling. AU - Valadez,Joseph J, AU - Berendes,Sima, AU - Lako,Richard, AU - Gould,Simon, AU - Vargas,William, AU - Milner,Susan, Y1 - 2015/10/19/ PY - 2015/10/4/entrez PY - 2015/10/4/pubmed PY - 2016/5/3/medline KW - Africa KW - South Sudan KW - equity KW - household survey KW - lot quality assurance sampling KW - millennium development goals KW - monitoring and evaluation KW - universal health coverage SP - 1711 EP - 21 JF - Tropical medicine & international health : TM & IH JO - Trop Med Int Health VL - 20 IS - 12 N2 - OBJECTIVES: We adapted a rapid monitoring method to South Sudan, a new nation with one of the world's highest maternal and child mortality rates, aiming to assess coverage of maternal, neonatal and child health (MNCH) services at the time of independence, and introducing a monitoring and evaluation system (M&E) for equity-sensitive tracking of progress related to Millennium Development Goals (MDG) 4 and 5 at national, state and county levels to detect local variability. METHODS: We conducted a national cross-sectional household survey among women from six client populations in all, but six of South Sudan's 79 counties. We used lot quality assurance sampling (LQAS) to measure coverage with diverse MNCH indicators to obtain information for national-, state- and county-level health system management decision-making. RESULTS: National coverage of MNCH services was low for all maternal and neonatal care, child immunisation, and child care indicators. However, results varied across states and counties. Central Equatoria State (CES), where the capital is located, showed the highest coverage for most indicators (e.g. ≥4 antenatal care visits range: 4.5% in Jonglei to 40.1% in CES). Urban counties often outperformed rural ones. CONCLUSIONS: This adaptation of LQAS to South Sudan demonstrates how it can be used in the future as an M&E system to track progress of MDGs at national, state and county levels to detect local disparities. Overall, our data reveal a desperate need for improving MNCH service coverage in all states. SN - 1365-3156 UR - http://www.nlm.medscape.idmu.unboundmedicine.unboundmedicine.com/medline/citation/26432978/Finding_the_gap:_revealing_local_disparities_in_coverage_of_maternal_newborn_and_child_health_services_in_South_Sudan_using_lot_quality_assurance_sampling_ L2 - https://doi.org/10.1111/tmi.12613 DB - PRIME DP - Unbound Medicine ER -