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1.
BMC Res Notes ; 17(1): 152, 2024 Jun 03.
Article in English | MEDLINE | ID: mdl-38831445

ABSTRACT

OBJECTIVE: The immunisation programme in Zambia remains one of the most effective public health programmes. Its financial sustainability is, however, uncertain. Using administrative data on immunisation coverage rate, vaccine utilisation, the number of health facilities and human resources, expenditure on health promotion, and the provision of outreach services from 24 districts, we used Data Envelopment Analysis to determine the level of technical efficiency in the provision of immunisation services. Based on our calculated levels of technical efficiency, we determined the available fiscal space for immunisation. RESULTS: Out of the 24 districts in our sample, 9 (38%) were technically inefficient in the provision of immunisation services. The average efficiency score, however, was quite high, at 0.92 (CRS technology) and 0.95 (VRS technology). Based on the calculated level of technical efficiency, we estimated that an improvement in technical efficiency can save enough vaccine doses to supply between 5 and 14 additional districts. The challenge, however, lies in identifying and correcting for the sources of technical inefficiency.


Subject(s)
Immunization Programs , Zambia , Immunization Programs/economics , Immunization Programs/statistics & numerical data , Humans , Efficiency, Organizational , Vaccination Coverage/statistics & numerical data , Vaccines/economics , Vaccines/supply & distribution
2.
Popul Health Metr ; 16(1): 13, 2018 08 13.
Article in English | MEDLINE | ID: mdl-30103791

ABSTRACT

BACKGROUND: The under-5 mortality rate (U5MR) is an important metric of child health and survival. Country-level estimates of U5MR are readily available, but efforts to estimate U5MR subnationally have been limited, in part, due to spatial misalignment of available data sources (e.g., use of different administrative levels, or as a result of historical boundary changes). METHODS: We analyzed all available complete and summary birth history data in surveys and censuses in six countries (Bangladesh, Cameroon, Chad, Mozambique, Uganda, and Zambia) at the finest geographic level available in each data source. We then developed small area estimation models capable of incorporating spatially misaligned data. These small area estimation models were applied to the birth history data in order to estimate trends in U5MR from 1980 to 2015 at the second administrative level in Cameroon, Chad, Mozambique, Uganda, and Zambia and at the third administrative level in Bangladesh. RESULTS: We found substantial variation in U5MR in all six countries: there was more than a two-fold difference in U5MR between the area with the highest rate and the area with the lowest rate in every country. All areas in all countries experienced declines in U5MR between 1980 and 2015, but the degree varied both within and between countries. In Cameroon, Chad, Mozambique, and Zambia we found areas with U5MRs in 2015 that were higher than in other parts of the same country in 1980. Comparing subnational U5MR to country-level targets for the Millennium Development Goals (MDG), we find that 12.8% of areas in Bangladesh did not meet the country-level target, although the country as whole did. A minority of areas in Chad, Mozambique, Uganda, and Zambia met the country-level MDG targets while these countries as a whole did not. CONCLUSIONS: Subnational estimates of U5MR reveal significant within-country variation. These estimates could be used for identifying high-need areas and positive deviants, tracking trends in geographic inequalities, and evaluating progress towards international development targets such as the Sustainable Development Goals.


Subject(s)
Child Health , Child Mortality , Data Collection/methods , Developing Countries , Health Status Disparities , Infant Mortality , Spatial Analysis , Bangladesh/epidemiology , Cameroon/epidemiology , Censuses , Chad/epidemiology , Child Mortality/trends , Child, Preschool , Developing Countries/statistics & numerical data , Humans , Infant , Infant Death , Infant Mortality/trends , Infant, Newborn , Mozambique/epidemiology , Uganda/epidemiology , Zambia/epidemiology
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