| Literature DB >> 23921987 |
Thyra E de Jongh1, Joanne H Harnmeijer2, Rifat Atun2, Eline L Korenromp2, Jinkou Zhao2, John Puvimanasinghe2, Rob Baltussen2.
Abstract
BACKGROUND: Since 2002, development assistance for health has substantially increased, especially investments for HIV, tuberculosis (TB) and malaria control. We undertook a systematic review to assess and synthesize the existing evidence in the scientific literature on the health impacts of these investments. METHODS ANDEntities:
Keywords: Africa; Asia; Health financing; developing countries; donors; health outcomes; impact
Mesh:
Year: 2013 PMID: 23921987 PMCID: PMC4124244 DOI: 10.1093/heapol/czt051
Source DB: PubMed Journal: Health Policy Plan ISSN: 0268-1080 Impact factor: 3.344
Figure 1Causal-chain framework, showing the temporal and logical effects of programme investments on health impacts, and the causal-chain elements for which data were provided in each of the included studies. If an element has been reported, this has been indicated by highlighting the corresponding segment in the same shade as the element shown in the framework. Elements that were not reported have been left unshaded. Note: Based on the Global Fund 5-year evaluation study framework (Macro International Inc. 2009)
Figure 2Flow chart showing selection process for included studies
Summary of health outcomes and impact measures reported in included studies
| Indicator category | Indicator | Studies reporting indicator |
|---|---|---|
| Service coverage | ART coverage | |
| TB case detection and notification rates | ||
| % of households owning at least one (long lasting) insecticide treated net | ||
| % of pregnant women receiving at least two doses of Intermittent Preventive Therapy | ||
| Service utilization | % of children under-5 years sleeping under an insecticide-treated bed net | |
| ART adherence and loss to follow-up rates | ||
| Health impacts | HIV infections averted | |
| HIV prevalence | ||
| Deaths due to HIV/AIDS | ||
| TB treatment outcomes | ||
| Malaria cases | ||
| Anaemia cases | ||
| Malaria-attributed mortality | ||
| All-cause adult mortality | ||
| All-cause under-5 mortality | ||
| Lives saved |
Summary and key findings of included studies
| Study (year) | Study design | Study setting | Evaluation period(s) | Funding source | Funded activities | Key findings |
|---|---|---|---|---|---|---|
| Controlled before–after study | Africa; 41 countries | 1997–2002 vs 2004–07 | PEPFAR | HIV prevention and treatment, infrastructure | • The annual change in HIV-related deaths was lower by 10.5% in PEPFAR countries compared with controls (95% CI: −16.6% to −4.4%, • There was no significant difference in the annual growth in the number of PLHIV, nor in the change in HIV prevalence over the evaluation period, between PEPFAR focus countries and controls. | |
| Time series study | Malawi; 1 district | 2002–08 | GF | ART in a ‘public health’ approach | After introduction of a GF HIV grant, in June 2005: • All-cause mortality (15–59 years), which was 10.2 per 1000 person-years in the pre-ART period (2002–05), fell by 16% in ART period 1 (2005–06) and by 32% in ART period 2 (2006–08). • AIDS mortality rate fell from 6.4 per 1000 person-years in the pre-ART period to 4.6 in ART period 1 and to 2.7 in ART period 2. • There was little change over time in non-AIDS mortality. • Treatment coverage among individuals eligible to start ART reached 70% in 2008. | |
| Observational study, with regression modelling | India; 6 states | 2003–08 | Bill and Melinda Gates Foundation (BMGF) | HIV prevention in high-risk groups, especially sex workers | • The programme was associated with reductions in HIV prevalence from 2003 to 2008 in all six states, ranging from 12.7% to 2.4% decline. • In three out of six states the amount of grant per PLHIV was significantly associated with lower HIV prevalence among the adult population, based on extrapolation from antenatal clinic data. • The estimated 100 178 HIV infections were averted between 2003 and 2008 as a result of the programme. | |
| Cohort study, retrospective | Kenya; 17 health facilities | 2001–06 | PEPFAR | ART | With the support of PEPFAR funding: • Mean monthly ART enrolment increased from 64 to 815 patients. • Patients enrolled in treatment in progressively earlier states of HIV disease, as indicated by increasing median CD4 cell count ( • Time from enrolment to treatment initiation decreased ( | |
| Observational study, with regression modelling | China; 3492 counties | 2001–08 | GF, World Bank | All aspects of TB control inc. TB drugs, lab strengthening, training, computers, and vehicles), health promotion materials | • From 2002 to 2005 case notification increased in all areas, and then stabilized or began to fall. The increases were much bigger in areas supported by the World Bank (236%) and Global Fund (224%) than in areas that only received Chinese government support (65%). • The average cost per TB case notified was similar in World Bank, Global Fund, and Chinese government areas. | |
| Cohort study, retrospective | Cameroon; 1 district hospital | 2003–08 | GF | Training in DOTS, lab strengthening, waiver of TB treatment and HIV testing fee | Compared with Phase A (2003–05), after introduction of a Global Fund grant in Phase B (2006–08): • Case notification (all TB forms) increased from 102 to 191. • Case detection (new smear-positive cases) increased from 28.3% to 41.6%. • Treatment success rate (all forms) increased from 75.3% to 89.2%. • Default and mortality rates dropped to zero from maximum values (over 2003–05) of 15% and 23%, respectively. | |
| Regression modelling study | Sub-Saharan Africa; 34 countries | 2002–08 | GF, others | ITNs/LLINs, IRS | As Official Development Assistance for malaria control increased in the period 2002–08: • Distribution of ITNs increased from 9.7 million in 2002 to 46 million in 2008. • Average ITN/IRS household ownership increased from 8.3% to 33%. • Cumulatively, the estimated 237 971 lives (among children under 5) were saved due to ITN/IRS coverage increase. | |
| Time series study | Zanzibar; 6 health facilities | 1999–2003 vs 2008 | GF, PMI, others | ACT, ITNs/LLINs, IRS, IPTp | After programme scale-up: • Malaria deaths decreased by 90%, malaria in-patient cases by 78% and confirmed malaria out-patient cases by 99·5% (all • Among children under-5, anaemia in-patient cases decreased by 85% ( • In children under-5, the proportion of all-cause deaths due to malaria fell from 46% to 12% ( | |
| Case study | Zambia; country | 2000–08 | GF, USAID/PMI, BMGF, Japan International Cooperation Agency and others | ACT, ITNs/LLINs, IRS, IPTp, Rapid Diagnostic Testing | • Household ITN ownership tripled between 2001 and 2006, with 44% of households owning at least one ITN in 2006. ITN use doubled between 2004 and 2006, achieving use levels of 23% in young children and 24% in pregnant women. • Increasing ITN coverage was associated in time and location with reductions in parasitaemia (53%) and severe anaemia (68%) in children under-5. • 62% of pregnant women received at least two doses of IPTp vs 54% before scale-up. • Under-5 mortality fell from 168 to 119 per 1000 live births. | |
| Regression modelling study | Africa; 44 countries | 1999–2008 | All external funding for malaria | ITNs | Excluding four outlier countries, each US$1 per capita in malaria development assistance for health was associated with an increase in ITN household ownership coverage (5.3% points) and ITN use in children under-5 (4.6% points). | |
| Cohort study, prospective | Kenya; 4 districts | 2004–06 | GF, DFID | ITNs/LLINs | • The proportion of children under-5 who slept under a recently treated ITN in the previous night increased from 7.1% in 2004, to 23.5% in 2005 (after introduction of heavily subsidized nets), and to 67.3% in 2006 (after introduction of free mass distributed ITNs). • Socioeconomic inequity in net coverage progressively decreased. | |
Note: ACT = artemisinin-based combination therapy; ART = anti-retroviral therapy; IPTp = intermittent preventive therapy in pregnancy; IRS = indoor residual spraying; ITN = insecticide-treated net; LLIN = long-lasting insecticidal net; PLHIV = person living with HIV.
Summary of funding data reported in included studies
| Study | External funding | Other funding | Funding period | ||
|---|---|---|---|---|---|
| Source(s) | Amount | Source(s) | Amount | ||
| PEPFAR | US$ 15b (US$6 billion disbursed by 2007) | Governments, GF and other donors | Not specified | 2003–08 | |
| GF | Not specified | Not specified | 2004–? | ||
| Bill and Melinda Gates Foundation | US$ 258m | Government | US$460 million for phase 2 (1999–2006); US$ 2.5b for phase 3 (2007–12), of which two-thirds allocated for HIV prevention. | 2003–08 | |
| PEPFAR | US$ 6.5m + free ARVs | Not specified | 2004–? | ||
| GF, WB, others | WB + others US$ 432m; GF US$ 151m | Central and local government | US$ 159m | 2001–08 | |
| GF | US$ 5.8m | Government | Not specified | 2005–09 | |
| All development assistance for malaria control, including GF | US$ 1.9b, of which GF US$ 1.4b (as disbursed by 2008) | Not specified | 2002–08 | ||
| GF, PMI, others | Not specified | Government | Not specified | 2003–? | |
| GF, USAID/PMI, WB, and others | US$ 130m | Government | Not specified | 2003–08 | |
| All development assistance for malaria control | Not specified | Not specified | 2000–08 | ||
| DFID, GF | US$ 106m (DFID US$ 56m; GF US$ 17m) | Not specified | 2004–? | ||
Notes: aThe amounts reported are those that were allocated in the form of grants or donor pledges, unless specified otherwise. ARV = antiretrovirals; GF = The Global Fund to Fight AIDS, Tuberculosis and Malaria; PMI = The President’s Malaria Initiative; USAID = The United States Agency for International Development; WB = The World Bank.
bThe funding period refers principally to the period over which the external funding was provided. If the funding period over which stated other funding was provided differs, this has been indicated separately. If the included study only mentioned a starting year for the funding, without additional information regarding the duration of the funding period, this has been indicated by presenting the end year with?
cAmounts converted from Chinese Yen, using the conversion factor provided by Jia et al.