Since the inception of the Roll Back Malaria (RBM) movement in 1996 1, billions of health dollars have been committed by the international donor community to reduce the burden of malaria in Africa 2, estimated to be over a million deaths directly due to Plasmodium falciparum annually 3. However there are remarkably few documentations of changes in disease burden associated with increases in access and use of interventions funded by new international donor agency money.

In Kenya the expansion of coverage of both ITN and effective ACT therapy (artemether-lumefanthrine) has occurred very recently. Between 2004 and 2005 ITN coverage among children aged less than five years rose from 7% to 24% and by the end of 2006 had risen to 67% coverage 4. Despite delays in implementing the revised drug policy supporting the use of AL 5, over 85% of rural clinics had AL in stock between August and December 2006 6. Paediatric admission time-series from three Kenyan hospitals were assembled to explore the impact of parallel changes in intervention coverage and malaria disease burden.

Between January 1999 and March 2007 (8.25 years) admissions due to malaria have systematically declined at three sites along the Kenyan coast. These declines were examined in relation to possible changes in overall hospital utilization by a naturally growing paediatric population size and within and between year variations in rainfall. The fact that the significant decline in malaria admissions occurred against a significant rise in non-malaria admissions in Kilifi and Malindi and remained unchanged at Kwale during the surveillance period (Figure 1, right panel) suggests that the declining admissions due to malaria were specific to malaria. It could be argued that an increase in non-malaria cases might be attributed to a changing diagnostic pattern over the surveillance period with fewer misclassifications or more doctors accepting as true malaria test results. This cannot be ruled out at Malindi or Kwale but at Kilifi standardized diagnostic practices have applied to all paediatric admissions throughout the entire surveillance period and thus changes in the pattern of diagnosis seem an unlikely explanation for the trends observed.

The monthly incidence of malaria is coupled to seasonal rainfall patterns on the Kenyan coast. The addition of rainfall as a covariate to the model had no effect on the slope or intercept of seasonally corrected trend lines because rainfall patterns were shown to have remained relatively constant during the observation period with no significant increasing or decreasing trends observed in any of the study sites. Attributing the long-term reduction in malaria cases to a constant change in rainfall is implausible as there was no evidence of a substantial decline in rainfall except for the anomaly recorded in 2004/5, where rainfall was lower on average than that expected (Figure 3, right panel). This was however followed by a considerable substantial increase in amount of rainfall recorded in 2006. Despite this there was no associated increase in malaria admissions observed in 2006 or early 2007.

The use of three different hospital admission series increases the external validity of a single observation from one hospital. We consider the data from Kilifi as the diagnostic gold standard based on the use of microscopy and a discharge diagnosis supported by review of clinical notes. Using this as our point of reference, external validity of this result is provided by data from Msambweni (Kwale) and Malindi. It is reassuring then that a consistent declining pattern in malaria admission is maintained across all study sites lending weight to the strength of the findings. By 2006, annual malaria admissions had decreased by an average of 57% compared to 1999 across all sites.

There are several possible factors that might explain these observations and are considered as plausibility arguments, as proposed by Habicht 23 and Victora 24, rather than measurable correlates. The most notable programmatic change over the 8.25 years of surveillance has been the increasing use of ITNs 4. We have assembled a population adjusted estimate of the per capita ITN distribution patterns between 1999 and 2007 across the three districts combined (Figure 4). At the start of the observation period ITN distribution in all the three study sites was negligible. During the period 2001–2004, there was a steady increase in the cumulative per capita ITN distribution (Figure 4). One year after initiation of a retail sector programme (beginning of 2003), cumulative ITN distribution was estimated to be 3% per capita across the three districts. By December 2004, three months after the inception of an MCH clinic sales programme, cumulative ITN distribution was over 13 nets per 100 people. The largest increase occurred in September 2006 during the mass distribution campaign from an estimated 0.34 nets per capita in August 2006 to 0.49 nets per capita by September 2006. Extending the surveillance from 2006 into March 2007 corresponds to a period of highest ITN "coverage", implementation of a new effective first line treatment policy and increasing rainfall. Even so the anomaly in malaria admissions recorded was greatest during this period with an average of -79 in Kilifi, -34 in Malindi and -14 in Kwale. It should, however, be recognized that the decrease in malaria cases started before the major expansion of prevention coverage in 2006, reasons for this remain unclear.

Data on the serial use of prompt, effective antimalarial treatment in each of the three districts was not possible to assemble. However a semi-qualitative, temporal description of drug efficacy is possible in accordance with national first line recommendations for treatment between 1999 and 2007. Between January 1999 and early 2000 chloroquine was still the only available antimalarial in government clinics despite wide-spread resistance documented on the coast 25. Between mid-2000 and April 2006 sulphadoxine-pyrimethamine (SP) was the nationally recommended first line drug available in most government clinics and drug efficacy declined rapidly over this period in Kilifi and Kwale until most studies showed at least 25% failure rates when undertaken after 2002 2627. The policy was changed in April 2004 to artemether-lumefathrine (AL) but was not effectively implemented until December 2006 5. The efficacy of AL was defined in Kilifi as in excess of 94% in 2002–2003 28. Patient access to antimalarials within 48 hours of onset of symptoms has been documented in Kwale district in 2001 (15%) and 2006 (17%) (29; unpublished data), both representing very low estimates of prompt access and we assume not dissimilar to anticipated access figures for Kilifi and Malindi districts during the same period. However, the widespread availability of even sub-efficacious SP over-the-counter from 2000 onwards in Kwale 3031 and Kilifi 32 may have had a suppressive effect on clinical disease risks operating similar to strategies prompting intermittent presumptive treatment in young children 33.

The use of hospital data provides a useful indicator of the long-term and short-term impact of scaling-up malaria interventions. It is not possible to definitely attribute carefully controlled and adjusted changes in malaria admission rates to expanded coverage of preventative and curative interventions; however these seem to be the most parsimonious explanations for the observations reported here along the Kenyan coast.

EA Okiro assembled all the hospital data, developed the analytical models and wrote the manuscript; SI Hay provided technical support for the time-series models and contributed to the drafting of the manuscript; PW Gikandi supervised the collection of all the hospital data since 1999; SK Sharif was the Provincial Medical Officer for Coast province between 1999 and 2005 responsible for the delivery of services and collection of health information and contributed to the final draft of the manuscript; AM Noor was responsible for the assembly of the ITN data in each district and contributed the final manuscript; N Peshu and K Marsh were overall responsible for the data provided by Kilifi district hospital and contributed to earlier drafts of the manuscript. RW Snow was responsible for the conception and continued funding of the project and its overall scientific management, analysis, interpretation and preparation of the final manuscript. All authors read and approved the final manuscript.

Table 1

Footnote: The intercept refers to the seasonally adjusted level of malaria and non-malaria cases and rainfall at the start of the observation period. Models for malaria and non-malaria included a covariate for rainfall. The regressions were performed with Newey-West standard errors with a lag of two months for models with malaria and non-malaria case outcomes and a lag of one month for models with rainfall.

Table 2

Footnote: The intercept refers to the seasonally adjusted level of malaria cases at the start of the observation period. Models included a covariate for non-malaria cases and rainfall. The regression was performed with Newey-West standard errors with a lag of two months for models with malaria and non-malaria case outcomes.

Figure 4

Footnote: Information on net deliveries was assembled from a variety of sources for each district. We assumed that ITN coverage was less than 5% between January 1999 and December 2002. This position is supported by reviews of net use undertaken in Kenya during this period 34. In Kilifi district a large scale trial of ITN was completed in 1993 35 and by 1997 there were few net replacements or net re-treatments 36. From 2002 Population Services International (PSI) had launched a retail sector, social marketing campaign for ITN distribution 37. Annual sales figures for the coast were obtained from PSI for the period January 2002 through to December 2004. Toward the end of 2004 PSI delivered heavily subsidized ITN through clinics and monthly sales by geo-positioned clinics in each of the three districts were available for the period November 2004 to March 2007. In September 2006 the Ministry of Health launched a large-scale free distribution campaign of free ITN to children under the age of five years 4. Net distribution volumes were recorded per geo-located distribution point within each district. Finally, small-scale community distribution projects over the surveillance by the district heath management team, NGO's and philanthropic organizations were recorded through interviews with DHMT members and district stakeholders and recorded as volumes of distribution and month of delivery. Cumulative monthly ITN distribution volumes per district were computed per capita using population size estimates derived from national census data and annual growth rates. This was implemented with projected population growth rate curves from national inter-censal district-specific annual rates of net population increase derived in 1989 and 1999 38.