Performance of forecasting, warning and detection of malaria epidemics in the highlands of western Kenya

Abstract

On the 4th July 2002 a leading national newspaper in Kenya, the Daily Nation, ran the headline 'Minister sounds alert on malaria' in an article declaring the onset of epidemics in the highlands of western Kenya. There followed frequent media coverage with quotes from district leaders on the numbers of deaths, and editorials on the failure of the national malaria control strategy. The Ministry of Health made immediate and radical changes to national policy on treatment costs in the highlands by suspending cost-sharing. Development partners and non-governmental organisations also responded with a large increase in the distribution of commodities (approximately US$ 500 000) to support preventative strategies across the western highland region. What was conspicuous by its absence was any obvious effort to predict the epidemics in advance of press coverage.

Potential Predictability of Malaria in Africa Using ECMWF Monthly and Seasonal Climate Forecasts

“…This shows for the first time that climate forecasts may usefully extend the early warning available from environmental monitoring on a continental scale and reaffirms the potential importance of accurate climate information in Africa (Thomson et al 2011). It is important to emphasize that this study is a first step and is 1994Alonso et al (2011 Higher than usual transmission indicated in Kenyan highlands 1998 Lindblade et al (1999) Epidemic starts in Feb in Ugandan highlands; authors associate outbreak with rainfall anomalies 1998 Githeko and Ndegwa (2001) Epidemic in Kenya from Feb 1998, but high incidence also reported in Jun-Jul 1997Jones et al (2007 Epidemic in Tanzania highlands from Feb to Jun 1998, and high incidence also reported in summer of 1997 2002 Hay et al (2003a) Epidemic identified in Nandi and Kericho in Jun-Jul, with conditions returning to normal in August; normal transmission occurred in the Kisii and Gucha districts 2005 Cox et al (2007) Examines DHIS data from 2002 to 2006 for Kabale and identifies outbreaks in 2005 (timing not described) and 2006 (centered on Jun) but questions the authenticity of the latter outbreak by using confirmed data from a sentinel site 2010 Ototo et al (2011) Report vector densities over the period from Sep 2009 to Apr 2010, reporting peak vector densities in Jan-Feb 2010; no long-term dataset is available to determine whether conditions were anomalous 2010 Yeka et al (2012) Describes general transmission in Uganda; smear-positivity rates for children under 5 show relative peaks in Kanungu District (Kihihi) for Oct-Dec 2009 and May-Jul 2010 (their Fig. 4); no anomalies in selected high-transmission zones limited to identifying the potential skill in such a system.…”

“…In particular, Rogers et al (2002) highlighted the potential role of satellite monitoring of climate conditions in early-warning systems for malaria and called for improvements in disease-modeling capabilities to fulfill this potential. Hay et al (2003a) also affirmed that rainfall monitoring could lead to improved planning potential. This was demonstrated in a case study for the Kenyan highlands, which also showed that the seasonalforecast models at the time were inadequately skillful to extend the advance warning provided by rainfall observations (Hay et al 2003b).…”

“…Hay et al (2003a) also affirmed that rainfall monitoring could lead to improved planning potential. This was demonstrated in a case study for the Kenyan highlands, which also showed that the seasonalforecast models at the time were inadequately skillful to extend the advance warning provided by rainfall observations (Hay et al 2003b). The study also emphasized the fact that malaria case monitoring provided inadequate advance warning to implement mitigation actions, because outbreaks were only detectable once under way.…”

“…The range of the peak depends on the vector in question and assumptions about mortality that are in the model (Lunde et al 2013), but it is clear that in this range the malaria transmission will be relatively insensitive to temperature anomalies on the order of a degree, as compared with similar perturbations at the cooler or warmer limits of transmission, where malaria transmission probability changes more rapidly with temperature. Moreover, in highly endemic areas where the infant PR starts to saturate at high values, host dynamics are much more relevant for year-to-year variability, reducing sensitivity to interannual changes in climate (Hay et al 2001). Thus, even if the underlying climate predictions prove to be accurate in highly endemic areas, climate-driven malaria forecasts are likely to be of limited usefulness.…”

A Temporal-Spatial Analysis of Malaria Transmission in Adama, Ethiopia

“…Although studies have identified important climatic, seasonal, and demographic factors underlying large-scale spatial and temporal patterns of malaria epidemics in African countries, [6][7][8][9][10][11][12][13] thus far, attempts to develop predictive models of malaria epidemics, which are accurate on the local scale, have not met with success. 14,15 At present, there are few small-scale temporal-spatial studies of malaria incidence, particularly in urban highland area of Africa. Small-scale temporal-spatial studies of malaria transmission are therefore essential to target interventions toward transmission hot spots, which may shift seasonally within a given locale.…”