Table 1

Key characteristics and demographics of investment case study sites
Characteristics Philippines Indonesia India (Orissa state) Nepal
Northern Samar Province Eastern Samar Province Pasay City Sikka District Meruake District Tasikmalaya City Pontianak City Kendrapara District Rayagada District Terai Cluster Hills Cluster Mountain Cluster
Description Rural province in Philippines, with poor MNCH Outcomes and low fiscal capacity. Limited availability of delivery facilities and existing facilities are poorly supplied. Large proportion of births occurs unassisted at home. Rural province in Philippines, with poor MNCH Outcomes, higher fiscal capacity and lower population than Northern Samar. Limited availability of delivery facilities and existing facilities are poorly supplied. Large proportion of births occurs unassisted at home. Urban city in Philippines with relatively low mortality, but high levels of inequity in access. Large number of private facilities, but concerns about quality of care. Heavy load on public facilities from most disadvantaged population. Rural district on coast of East Nusa Tenggara province. Government has low fiscal capacity; population itself has low levels of education and high levels of poverty. ~10% of population live on isolated islands. Malaria is endemic. Rural district within Papua Province. Very remote with a high cost of living and limited access to clean water. ~50% of population live in difficult to access mountainous regions. Malaria is endemic. Urban city within West Java province with a very high population density. Government has low fiscal capacity, and a significant private sector exists. Traditional birth attendants still account for notable proportion of births. Capital City of West Kalimantan province. Large private sector, with significant number of private midwives. Health knowledge of population is poor, and levels of vaccination have dropped due to recent scare involving adverse effects. Rural, but not remote, coastal district in Orissa. Poor, with ~67% considered to have a low standard of living. Climatically vulnerable, with access to health services impeded on a seasonal basis. Considered typical of rural districts in coastal areas of Orissa. Remote, heavily forested tribal district in Orissa. Poor, with ~88% of population considered to have low standard of living. Sparse population and security issues inhibit access to health services. Malaria is endemic. Considered typical of tribal areas of Orissa. Cluster of disadvantaged districts within the Terai ecoregion. More densely populated than other ecoregions, with fewer access problems. Cluster of disadvantaged districts within the Hills ecoregion. Significant impact of ten year civil conflict in this cluster Cluster of disadvantaged districts within Mountain ecoregion. Sparsely populated, with many areas only accessible by air or foot.
Population 670000 440000 410000 300000 192000 642000 522000 1410000 820000 5680000 2340000 860000
(1) (1) (2) (3) (4) (5) (6) (7) (7) (8) (8) (8)
MMR (per 100 000 live births) 160 160 80 228 228 228 228 303 303 281 281 281
(9)Provincial estimate (10)Provincial estimate (2)City estimate (11)National estimate (11)National estimate (11)National estimate (11)National estimate (12)State estimate (12)State estimate (13)National estimate (13)National estimate (13)National estimate
NMR (per 1000 live births) 22 22 17 31 24 19 23 45.4 45.4 26 54 74
(14)Region 8 estimate (14)Region 8 estimate (2)City estimate (11)Provincial estimate (11)Provincial estimate (11)Provincial estimate (11)Provincial estimate (15)State estimate (15)State estimate (13)Cluster estimate (13)Cluster estimate (13)Cluster estimate
U5MR (per 1000 live births) 68 43 28 80 64 59 49 90.6 90.6 89.3 110 168.5
(9)Provincial Estimate (16)Provincial estimate (2)City estimate (11)Provincial estimate (11)Provincial estimate (11)Provincial estimate (11)Provincial estimate (15)State estimate (15)State estimate (13)Cluster estimate (13)Cluster estimate (13)Cluster estimate

Sources:

1. National Epidemiology Center. Field Health Service Information System Annual Report. Manila, Philippines: Department of Health2007.

2. Pasay City Health Office. Pasay City Vital Statistics. Manila, Philippines: Department of Health2008.

3. BPS - Kabupaten Sikka. 2008 Population Registration: BPS-Statistics Indonesia,2008.

4. BPS - Kabupaten Meruake. 2008 Population Registration: BPS-Statistics Indonesia,2008.

5. BPS - Kota Tasik. 2008 Population Registration: BPS-Statistics Indonesia,2008.

6. BPS - Kota Pontianak. 2008 Population Registration: BPS-Statistics Indonesia,2008.

7. Census of India. 2001; Available from: http://www.censusindia.gov.in webcite.

8. HMG Nepal, National Planning Commission Secretariat, Central Bureau of Statistics (CBS); UNFPA. Population Census 2001, National Report. 2002.

9. North Samar Provincial Health Office. Annual Report. Manila, Philippines: Department of Health2008.

10. East Samar Provincial Health Office. Maternal Death Review. Manila, Philippines: Department of Health2009.

11. Statistics Indonesia (Badan Pusat Statistik-BPS) and Macro International. Indonesia Demographic and Health Survey 2007. Calverton, Maryland, USA:: BPS and Macro International.2008.

12. Sample Registration System, Office of the Registrar General of India. Special Bulletin on Maternal Mortality in India 2004–062009.

13. Ministry of Health and Population, New ERA, ORC Macro International Inc. Nepal Demographic and Health Survey 20062007.

14. National Statistics Office. Philippines National Demographic and Health Survey 2008. Manila, Philippines2009.

15. International Institute for Population Sciences (IIPS). National Family Health Survey (NFHS-3) 2005–06, India. 2007;1(1–540).

16. East Samar Provincial Health Office. Annual Report. Manila, Philippines: Department of Health2008.

Jimenez Soto et al.

Jimenez Soto et al. BMC Public Health 2013 13:601   doi:10.1186/1471-2458-13-601

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