At Forum 2012, held in Cape Town in April 2012, a session was convened to explore the current roles and future potential of international partnerships in advancing African development through health research. Attendees sought to identify the elements of partnerships that would bring the greatest benefits to research and capacity development in Africa and, at the same time strengthen health and development systems on the continent. COHRED said that funders and research programmes must consciously build systems and capacity in their areas that can extend beyond silos and support other campaigns. Participants developed a number of specific and general recommendations. Most crucially, perhaps, research for health programmes must design capacity building for development and health systems into their programmes from the earliest stages, i.e., this must be a goal and not merely an incidental, even unexpected collateral benefit. Partnering organisations should be selected with attention to their commitment to ensuring that the infrastructure and human expertise which will be developed for the programme is sustainable and transferable. Country ownership will benefit from locally anchored partners, such as national universities, who will still be there when a particular research programme is concluded.
Monitoring equity and research policy
In this global review, researchers aimed to determine which countries are experiencing gaps in health research, identifying Chad, Angola, DRC, Sudan, Lesotho, Rwanda, Madagascar, Algeria, and the Central African Republic as African countries with the lowest levels of health research. Efforts to strengthen capacity in health research have, so far, concentrated on countries where there is existing capacity rather than those where it is almost completely lacking. Judged by absolute numbers of scientific papers, those with the fewest are mainly small islands and a few countries that are politically isolated. Judged by papers per capita, the lowest include countries in the former Soviet Union and Africa, both regions experiencing declines in life expectancy in recent years, and states experiencing conflict. Although there is a positive association between economic development and research output, some relatively wealthy countries seriously underperform. There are many examples of good practice, including regional networks and international partnerships. The authors present a strong argument for external funders to look to the long term and consider how best to build health research capacity where it is virtually absent.
In this study, the Lives Saved Tool (LiST) model was used to quantify the likely impact that malaria prevention intervention scale-up has had on malaria mortality over the past decade (2001-2010) across 43 malaria endemic countries in sub-Saharan African. The likely impact of insecticide-treated nets (ITNs) and malaria prevention interventions in pregnancy (intermittent preventive treatment [IPTp] and ITNs used during pregnancy) over this period was assessed. Results indicated that malaria prevention intervention scale-up over the past decade has prevented 842,800 child deaths due to malaria in the 43 countries, compared to a baseline of the year 2000. Over the entire decade, this represents an 8.2% decrease in the number of malaria-caused child deaths that would have occurred over this period had malaria prevention coverage remained unchanged since 2000. The biggest impact occurred in 2010 with a 24.4% decrease in malaria-caused child deaths compared to what would have happened had malaria prevention interventions not been scaled-up beyond 2000 coverage levels. ITNs accounted for 99% of the lives saved. The results suggest that funding for malaria prevention in Africa over the past decade has had a substantial impact on decreasing child deaths due to malaria. Rapidly achieving and then maintaining universal coverage of these interventions should be an urgent priority for malaria control programmes in the future, the authors argue. Successful scale-up in many African countries will likely contribute substantially to meeting Millennium Development Goal (MDG) 4 to reduce child mortality, as well as succeed in meeting MDG 6 (Target 1) to halt and reverse malaria incidence by 2015.
Little is known about the burden of influenza in sub-Saharan Africa. Routine influenza surveillance is key to getting a better understanding of the impact of acute respiratory infections on sub-Saharan African populations. To address this gap, a project called Strengthening Influenza Sentinel Surveillance in Africa (SISA) was launched in Angola, Cameroon, Ghana, Nigeria, Rwanda, Senegal, Sierra Leone and Zambia. It aimed to help improve influenza sentinel surveillance, including both epidemiological and virological data collection, and to develop routine national, regional and international reporting mechanisms. These countries received technical support through remote supervision and onsite visits. Consultants worked closely with health ministries, the World Health Organization, national influenza laboratories and other stakeholders involved in influenza surveillance. Working documents such as national surveillance protocols and procedures were developed or updated and training for sentinel site staff and data managers was organised. The main lesson emerging from SISA is that targeted support to countries can help them strengthen national influenza surveillance, but long-term sustainability can only be achieved with external funding and strong national government leadership.
In this paper, the authors outline the process of developing country-specific spreadsheet-based models to explore the financial resource requirements of health system reform options in South Africa and Tanzania. Their intention is to provide guidance for analysts who wish to develop their own models, and to illustrate, with reference to the South African and Tanzanian modelling experience, how one has to adapt to data constraints and context-specific modelling requirements. They found that using modelling to assess the financial feasibility and implications of alternative health system reform paths can be of great value in supporting evidence-informed policy-making. Developing one's own spreadsheet model has a number of advantages, including allowing greater flexibility to reflect specific country circumstances and requiring the analyst to carefully evaluate the assumptions built into the model. A pragmatic approach should be adopted in data scarce contexts, but all assumptions should be made explicit and justified. A major advantage of the modelling process is that it can highlight priority areas for improved data collection.
Recent estimates of malaria-attributable under-five deaths prevented using the Lives Saved Tool (LiST) confirm the substantial impact and good cost-effectiveness that insecticide-treated nets (ITNs) and indoor residual spraying have achieved in high-endemic sub-Saharan Africa. ITNs, the author argues, have an additional indirect mortality impact by preventing deaths from other common child illnesses, to which malaria contributes as a risk factor. As conventional ITNs are being replaced by long-lasting insecticidal nets and scale-up is expanded, additional lives may be saved, and these figures may be calculated using LiST. LiSt combines key indicators for time trend analysis with dynamic transmission models, fitted to long-term trend data on vector, parasite and human populations over successive phases of malaria control and elimination. The author argues that policy makers and programme planners should use LiST as a planning tool, but notes that this will require enhanced monitoring and evaluation of the national programme and its impact.
Because of increased global trade and travel, micro-organisms now travel globally faster than before. To track these microorganisms, whole genome sequence analysis is the ideal instrument, but to make effective use of the results a global genomic database for microorganisms is needed. In this editorial, the author argues that the introduction of genomic testing represents a giant step forward for developing countries in the fight against infectious diseases. He compares the introduction of this new technology to the spread of cellphones, which made expensive and exclusive landlines unnecessary and made communication possible for everybody. Similarly, identification and typing of microorganisms will suddenly become technically and economically feasible, enabling control and prevention efforts previously missing in many regions. At the same time, developing countries moving to use this technology will not need to develop expensive, specialised lab systems, since microbiological lab work will basically be the same for TB, enterobacteria, viruses, etc. The author calls on developing countries to participate in this process from the start.
The main aim of this study was to determine how data on water source quality affect assessments of progress towards the 2015 Millennium Development Goal (MDG) target on access to safe drinking-water. Data was collected from five countries on whether drinking-water sources complied with World Health Organisation water quality guidelines on contamination with thermotolerant coliform bacteria, arsenic, fluoride and nitrates in 2004 and 2005. Taking account of data on water source quality resulted in substantially lower estimates of the percentage of the population with access to safe drinking-water in 2008 in four of the five study countries: the absolute reduction was 11% in Ethiopia, 16% in Nicaragua, 15% in Nigeria and 7% in Tajikistan. There was only a slight reduction in Jordan. Microbial contamination was more common than chemical contamination. The authors warn that the WHO criteria used to determine whether a water source is safe can lead to substantial overestimates of the population with access to safe drinking-water and, consequently, also overestimates the progress made towards the 2015 MDG target. Monitoring drinking-water supplies by recording both access to water sources and their safety would be a substantial improvement.
The authors of this study assessed the feasibility of using birth attendants instead of bereaved mothers as perinatal verbal autopsy respondents in low- and middle-income countries. Verbal autopsy interviews for early neonatal deaths and stillbirths were conducted separately among mothers (reference standard) and birth attendants in 38 communities in four developing countries, including the Democratic Republic of Congo and Zambia. For early neonatal deaths, concordance between maternal and attendant responses across all questions was 94%. Concordance was at least 95% for more than half the questions on maternal medical history, birth attendance and neonate characteristics. Concordance on any given question was never less than 80%. For stillbirths, concordance across all questions was 93%. Concordance was 95% or greater more than half the time for questions on birth attendance, site of delivery and stillborn characteristics. Overall, the causes of death established through verbal autopsy were similar, regardless of respondent. In conclusion, birth attendants can substitute for bereaved mothers as verbal autopsy respondents.
Incidence is a better measure than prevalence for monitoring AIDS, but it is not often used because longitudinal HIV data from which incidence can be computed is scarce. The objective of this study was to estimate the force of infection and incidence of HIV in Malawi using crosssectional HIV sero-prevalence data from the Malawi Demographic and Health Survey conducted in 2004. The researchers estimated population incidence from the force of infection by accounting for the prevalence, as the force of infection applies only to the HIV-negative part of the population. The estimated HIV population incidence per 100,000 person-years among men is 610 for the 15–24 year age range, 2,700 for the 25–34 group and 1,320 for 35–49 year olds. For females, the estimates are 2,030 for 15–24 year olds, 1,710 for 25–34 year olds and 1,730 for 35–49 year olds. In conclusion, the researchers assert that their method provides a simple way of simultaneously estimating the incidence rate of HIV and the age-specific population prevalence for single ages using population-based crosssectional sero-prevalence data. The estimated incidence rates depend on the HIV and natural mortalities used in the estimation process.