Malaria not only remains a leading cause of morbidity and mortality, but it also impedes socioeconomic development, particularly in sub-Saharan Africa. Rapid and unprecedented urbanization, going hand-in-hand with often declining economies, might have profound implications for the epidemiology and control of malaria, as the relative disease burden increases among urban dwellers. Reviewing the literature and using a modeling approach, we find that entomologic inoculation rates in cities range from 0 to 54 per year, depending on the degree of urbanization, the spatial location within a city, and overall living conditions. Using the latest United Nations figures on urbanization prospects, nighttime light remotely sensed images, and the “Mapping Malaria Risk in Africa” results on climate suitability for stable malaria transmission, we estimate that 200 million people (24.6% of the total African population) currently live in urban settings where they are at risk of contracting the disease. Importantly, the estimated total surface area covered by these urban settings is only approximately 1.1–1.6% of the total African surface. Considering different plausible scenarios, we estimate an annual incidence of 24.8–103.2 million cases of clinical malaria attacks among urban dwellers in Africa. These figures translate to 6–28% of the estimated global annual disease incidence. Against this background, basic health care delivery systems providing early diagnosis and early treatment and preventive actions through mother and child health programs and the promotion of insecticide-treated bed nets for the rapidly growing numbers of the urban poor must be improved alongside well-tailored and integrated malaria control strategies. We propose environmental management and larviciding within well-specified productive sites as a main feature for such an integrated control approach. Mitigation of the current burden of malaria in urban African settings, in turn, is a necessity for stimulating environmentally and socially sustainable development.
Malaria is responsible for an estimated 300–500 million clinical attacks globally, and >1 million deaths each year mainly among children less than five years of age living in sub-Saharan Africa. The disease accounts for an estimated loss of 44.7 million disability adjusted life years (DALYs), more than 80% of which are currently concentrated in sub-Saharan Africa.1 In the absence of effective intervention strategies and the rapid spread of drug resistance, the number of malaria cases might double over the next 20 years.2 Acute febrile illness, chronic debilitation, complication of pregnancy, and impairment of the physical development and learning ability of children are typical consequences of malaria, and represent a huge negative social impact in the high burden areas.3 Furthermore, the macroeconomic toll is severe, particularly in sub-Saharan Africa, since malaria may cost more than one percentage point of economic growth every year.4
The demographic changes that we experience today are profound. Rapid urbanization alters the frequency and transmission dynamics of malaria, with significant effects on disease-associated morbidity and mortality, which in turn has important implications for control.5, 6 At present, the least developed countries experience the highest urbanization rates, often in the range of 2–6% per year.7 Until recently, urban development was generally believed to reduce the risk of vector breeding, and thus malaria transmission. However, many African countries have declining economies, and most cities are struggling to cope with the pace and the extent of urbanization. Poor housing and lack of sanitation and drainage of surface water can increase vector breeding and human vector contact, and thus pose unique challenges for control.8, 9 Furthermore, the adaptation of malaria vectors to urban areas has been well documented for at least two decades,10 and local transmission has been conclusively demonstrated in many African cities.6 An additional problem on the human side is that a high proportion of the urban population may be at risk of severe disease due to delayed acquisition or lack of protective immunity.
Quantitative assessment of the malaria burden in urban areas together with information on socially and environmentally sound and cost-effective intervention strategies are urgently required. These data will provide a rational basis for the design, implementation, and monitoring of malaria control programs.11 Especially in urban environments a high degree of heterogeneity is observed: urban dwellings typically offer a relatively narrow spectrum of focal breeding sites. These sites are often straightforward to identify and to access, providing opportunities to spatially targeting interventions.12 A great impact on urban malaria could be achieved by eliminating key risk sites. Consequently, techniques of environmental management, particularly surface water management, within the frame of an integrated control approach, offer potentially sustainable methods to substantially reduce transmission.
The purpose of this paper is to assess and quantify the current burden that malaria imposes on urban Africa and to propose mitigation strategies. In the first section, we review urban development in Africa over the past 50 years and highlight key predictions for the next 30 years. We then develop methodologies for estimating the surface area and the number of people living in African cities that are at risk of malaria transmission, employing the latest United Nations (UN) figures on urbanization prospects, results from the “Mapping Malaria Risk in Africa” (MARA) network on climate suitability for stable malaria transmission, and nighttime lights satellite images. We provide a systematic review of the published literature on malaria prevalence and entomological inoculation rate (EIR), including new estimates of EIR in urban African settings. We describe the key malaria vectors and their habitats. In an attempt to estimate the total number of annual malaria cases in urban Africa, we examine the relationship between EIR and annual malaria incidence. We link these data with the number of people living in varying urban environments and characterized by distinct EIR. The last section discusses issues in strengthening current control programs, by using an integrated approach consisting of early diagnosis and prompt treatment and the distribution of insecticide-treated bed nets (ITNs) as the backbone, coupled with environmental management, as a key feature to mitigate the current burden of malaria in urban African settings.
Urbanization in Africa
The classification of urban environments is by no means uniform. Urban communities may be defined by physical borders, population size, geographic limits associated with administrative responsibilities, or governance.13 In Botswana, for example, urban areas are defined as agglomerations of 5,000 or more inhabitants, with the majority depending on non-agricultural activities. In Ethiopia, however, localities of 2,000 or more people are classified as urban, and in Malawi all townships, town planning areas, and all district centers are defined as urban.14 Usually inhabitants at the urban fringe are not included in the urban statistics because they are not part of a legally proclaimed area, although these areas often experience the highest population growth rates.
In Africa, many cities were developed as colonial administrative or trading centers rather than industrial and commercial zones equipped to support large populations. Urban authorities have often been unable to keep up with the rapid growth of squatter communities and shantytowns. Furthermore, stagnating and declining economies have often led to a decrease in the quality of the urban environment and deterioration in both the quality and distribution of basic services, including housing and medical facilities. As a result, urban environments exhibit significant spatial variation in their development level. Well-developed city centers are often surrounded by underdeveloped and inadequately serviced settlements supporting a large fraction of the population.
To date, the African continent is considerably less urbanized when compared with the rest of the world. For example, in the year 2001 urban dwellers in East Africa accounted for only 25% of the population ( Table 1), compared with 70% and above elsewhere in the world. Current estimates by the UN predict that half of the African population will live in urban settings by the year 2025, and that the percentage will further increase to 52.9% or 787 million in 2030.7 In contrast, the rural population will experience a slower growth: from 498 million in 2000 (52.8%) to an expected 702 million in 2030 (47.1%). There are two underlying reasons. First, there are strong rural-urban economically driven migrations with people seeking education and job opportunities outside subsistence farming. Second, rural settlements have evolved into small or medium size cities. In 1950, there was not one single megacity (defined as places with ≥750,000 inhabitants) on the African continent. Fifty years later there were 43 megacities, already harboring 11.9% of the African population. It is estimated that in 2010 more than 100 cities on the African continent will have a population of at least 500,000, and more than half of them will be inhabited by more than one million people.7
Materials and Methods
Urban population estimates in malaria endemic areas
We calculated the total number of urban dwellers living in African countries that are endemic for malaria, using the MARA map on the predicted suitability of malaria transmission in Africa, and the most recent UN data on urban populations.7 Based on population density maps we have included Chad, Kenya a Mali, and Niger in our estimate because their major urban centers, namely N’Djamena, Nairobi, Bamako, and Niamey, are located in areas where malaria transmission occurs. We have added the urban population of Sudan because new evidence suggests that focal malaria transmission has become established in Khartoum.15 Approximately 74% of the population is at risk of acquiring the disease.16 We have also included the urban populations of Eritrea and Ethiopia because recent research has shown that malaria has become a major public health problem with 92% and 40% of their population, respectively, at risk.16, 17
Surface estimates of malaria-endemic urban Africa
In the absence of precise data on surface areas of urban Africa, we used information on clusters of nighttime stable lights classified as human settlements as a proxy for urbanization. The data was collected by the U.S. Air Force Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) during a six-month period between October 1994 and March 1995. The data are publicly available on the web-site http://dmsp.ngdc.noaa.gov/html/download.html. The OLS has a unique low-light imaging capability, which detects and distinguishes lights from human settlements, wildfires, gas flares, or fishing boats.
On average, only 41.5% of the urban housing units in malaria-endemic Africa have electricity, ranging from as low as 39% in Côte d’Ivoire and Ghana, to a maximum of 92% in Rwanda (http://www.afdb.org/knowledge/statistics/statistics_indicators_gender/poverty/pdf/tab2_9.pdf). There are further variations in the connection to the power grid between and within cities. For example, in Tanzania, the percentage of households reporting connection to the power grid in urban areas ranges from 19% to 45%. In addition, the average African electricity use per capita was estimated to be only 620 kilowatt-hours (kwH) in 1997, which corresponds to only 30.2% of the world electricity use per capita and only 7.7% of the high income countries’ electricity use per capita (e.g., the electricity use per capita for the United States in 1997 was 11,700 kwH).18– 20 Therefore, without any correction factor, the use of nighttime light data as a proxy for African urbanization would considerably underestimate surface areas.
On the basis of statistics on the distribution and consumption of energy in Africa as discussed earlier, we propose to multiply the surface estimates by factors equal to two and three to obtain more reasonable figures for a lower and an upper bond, respectively.
Entomologic inoculation rates, malaria prevalence, and vectors in urban Africa
We generated a comprehensive database on malaria transmission in urban and peri-urban African settings, as expressed by EIR and malaria prevalence. The EIR is defined as the number of infective bites per person per time unit. Two previous papers have compiled EIRs for urban and rural settings in sub-Saharan Africa.6, 21 We updated and extended these compilations by performing a computer-aided systematic search of published work on urban malaria in Africa on MEDLINE®(U.S. National Library of Medicine, Bethesda, MD) and consulting with representatives from the MARA network on malaria prevalence data across Africa. Although studies of malaria transmission in urban areas date back more than 100 years, we have focused on the last 25 years because older studies might not be representative for the current situation. We only included data from urban areas that have a population of 10,000 inhabitants or more.
In many instances, we estimated EIRs from age-specific malaria prevalence data using the mathematical model of the Garki project.22 This method has been recently described by Hagmann and others.23 Briefly, the Garki model is a dynamic model for Plasmodium falciparum transmission and infection that was originally fitted to data from Garki district in northern Nigeria and collected as part of a major trial of indoor residual spraying and mass chemoprophylaxis.24 The mathematical model22 treats the human population as made up of individuals in each of seven distinct compartments defined by infection and immunologic status and consists of an algorithm for predicting the proportion of the human population at each age in each of these compartments, as a function of the vectorial capacity C. It is defined by a set of difference equations that specify the change in each of these proportions from one time point to the next. Within this model, the EIR is approximated by the product C*y 1 , where y 1 is the proportion of the human population that is infective. To estimate the EIR from community parasitologic survey data, the equilibrium age-prevalence curves for the Garki model were estimated for different values of C, using a golden section search routine to locate the maximum likelihood estimate.25 Asymptotic 95% confidence estimates were obtained by numerical estimation of the Fisher information. This procedure gives minimum estimates of the EIR because the model was developed on the assumption that none of the infections are treated. Infections that are treated soon after becoming patent do not contribute to the pool of prevalence in the community; thus they are additional to those that contribute to the EIR estimate and the true EIR is higher by a rate equal to the incidence of the treated infections. We also implemented the simple version of the model that assumes a constant vectorial capacity throughout the year. This also leads to lower estimates of the EIR than would be obtained if seasonal transmission was assumed.
We also reviewed the literature with regard to the main malaria vectors and summarize their habitat preferences, particularly for the larval stages.
Annual malaria cases in urban Africa
For the estimation of urban African malaria cases, we compiled data from the literature reporting both EIRs and annual malaria incidence rates in children less than seven years old (calculated from parasitologic survey data, and ideally including the proportion of cases observed in health facilities) in urban or rural settings in Africa. In two studies, EIRs were determined previously and published elsewhere.21 Only surveys conducted over a period of at least nine months, and which classified malaria as a febrile episode (usually defined as an axillary temperature ≥ 37.5°C) and detectable parasitemia were considered. We examined the relationship between EIR and annual malaria incidence by plotting data from each site on linear (incidence) and logarithmic (EIR) axes, and by performing a linear regression analysis.
Population at risk and surface of malaria transmission in urban Africa
Figure 1 depicts the malaria-endemic area of Africa, using nighttime lights as a proxy for urban areas and megacities. Table 2 presents selected key figures for the population and surface area of Africa in general, and more specifically for its urbanized areas at risk of malaria transmission. Our surface estimates based on data of nighttime lights images, corrected by factors of 2–3 show that urban areas in Africa represent 1.7–2.6% of the total continent’s surface. The estimated urban surface in Africa at risk of malaria transmission is 330,500–492,800 km2, accounting for 1.1–1.6% of the total surface area of Africa. At present, 96.8 million Africans live in 43 megacities, 28 of which are located in areas of malaria transmission. The total surface area of these 28 megacities calculated on the basis of their administrative boundaries covers only 0.08% of the total continent’s surface.
We estimate that 200 million people currently live at risk of contracting the disease in urban Africa (24.6% of the total African population).
Malaria prevalences, EIRs, and malaria vectors in urban Africa
Table 3 presents a comprehensive summary of all studies pertaining to urban and peri-urban malaria in Africa that met our inclusion criteria. We further present the calculated EIR values (marked with *). We find that urban areas are characterized by low malaria transmission. The EIR estimates in city centers approach zero, indicative of very low malaria transmission. In contrast, EIRs as high as 54 have been found in peri-urban areas, depending upon rainfall patterns, temperature, geographic location, and dominant land-and water-use patterns. In close proximity to rice paddies in Bouaké, Côte d’Ivoire, characterized by marshland and many streams, an annual EIR of 126 was determined.26 Dispersion of anophelines, was demonstrated to be low, with the large majority of adult Anopheles gambiae collected within 200–300 meters from their main breeding sites.27, 28 A recent, longitudinal study in Kampala, Uganda has found a highly heterogenous malaria risk with proximity to breeding places as the strongest predictor of clinical malaria.29
Malaria prevalence rates also show large variation. They may range from as low as 1% in city centers to more than 90% in suburbs. A high malaria prevalence of up to 50% within all age groups was recorded in peri-urban areas of Niamey, Niger during the rainy season30 compared with only 5% in the dry season. A study in Yaoundé, Cameroon re ported a high malaria prevalence, which could be explained by urban aquaculture practice and house locations proximal to wetlands.31 Any increase in transmission due to ecologic transformation or climatic changes could therefore contribute to malaria epidemics. As might be expected, comparative appraisal of malaria prevalence rates in rural and urban settings showed significantly higher rates in rural environments; up to four-fold higher in some areas.28, 32
Table 4 summarizes the key features of the five main Anopheles species capable of transmitting malaria in urban Africa, with particular emphasis on their larval habitat preferences. Viable environmental control measures against urban vector breeding sites are also summarized in Table 4. Prominent among them are land filling or drainage work, flooding, or vegetation management.
Malaria incidence in urban Africa
Linear relationship between malaria incidence and EIR
We identified eight studies (three urban and five rural data points) that met all our inclusion criteria. We assume that the relationship between EIRs and incidence rates obtained from these data can be applied to all age groups in urban settings. This might be justified because all age groups are similarly susceptible to the disease, which is in sharp contrast to rural settings where children less than five years of age and pregnant women are at highest risk of disease-attributable morbidity and mortality.33 The obtained data supported a linear relationship between malaria incidence and the logarithm of annual EIR with r2=0.74 (Figure 2). The linear regression analysis fitted to malaria incidence data obtained from community surveys and EIR obtained in the same settings resulted in the following equation: Annual malaria incidence (per 1,000) = 408 log10 (annual EIR) + 153.
Malaria incidence in different urban environments
The urban poor are found to face similar health risks when compared with the general rural population. Poor people are at increased risk both of becoming infected with malaria and of becoming infected more often.16 According to recent evidence, households characterized by extreme poverty and unsatisfactory basic services account for more than 40% in African cities (http://www.johannesburgsummit.org/html/media_info/pressreleases_factsheets/wssd10_africa.pdf). Therefore, we split the total urban African population in malaria endemic areas (our estimate of 200 million) into 80 million poor (40%) and 120 million (60%), living in more satisfactory conditions. We divide the poor urban Africans into two sub-groups according to their geographic origin. Approximately 10.5% of these (8.4 million) live in unstable, fringe, or epidemic malaria transmission areas,34 which are exposed to very low EIRs of approximately 0–1. The remaining 89.5% (35.8 million) urban poor live in high malaria transmission zones where, as we have summarized in Table 3, EIRs range between 3 and 30 (e.g., Kinshasa35). Those 120 million of urban Africans living in areas with adequate conditions, thus at low malaria risk, are exposed to few infective bites per year ( Table 3), resulting in EIRs of 0–4.
With assistance of the estimated linear relationship and the assigned EIR to the African population living in three distinctively different urban environments we estimate that 24.8–103.2 million malaria cases occur annually in urban Africa. First, in the poor environments in low transmission areas, 0–1.3 million cases of malaria are likely to occur annually. Second, 0–47.8 million malaria cases are expected to occur among the 120 million residents of standard urban housing areas in high transmission areas. Third, the largest number of annual cases, namely 24.8–54.1 million, occurs in environments characterized by high malaria transmission and poverty (Figure 3).
A better understanding of the dynamic process of urbanization, including urban risk factors for health, might lead to the development of suitable health interventions and preventive measures for the rising number of urban inhabitants. We have presented an overview of urbanization trends in Africa and the epidemiology of malaria in these settings. We estimate that about 200 million urban dwellers are currently at risk of malaria. These people are concentrated on a total surface area of less than 500,000 km2, representing a maximum of 1.6% of the entire African continent. Consequently, population density in these settings is high, with an average of 400 inhabitants/km2. We estimate that 24.8–103.2 million clinical malaria episodes occur annually in urban settings that are endemic for malaria. Since the current estimated global malaria incidence is on the order of 300–500 million cases annually, our estimates indicate that 6–28% of these cases occur in urban African environments. The contribution of malaria to social hardship and heavy economic losses resulting from high health care expenditures and loss of work productivity are increasingly acknowledged.4 Our review also shows that the epidemiology of malaria in the urban areas is not fully comparable to what is well established for rural settings. For example, urban malaria is characterized by much greater heterogeneity, owing to the dynamic demographic and environmental conditions. Consequently, understanding the spatial and temporal pattern of urban malaria risk will facilitate the design of well-tailored integrated urban malaria control programs.
There is a large body of historical evidence about great achievements of integrated malaria control in urban areas, predating by several decades the advent and large-scale application of DDT. Control measures were largely targeted at the larval stages of malaria vectors by means of source reduction. Application of oil and larvicides on open water bodies often complemented environmental control interventions. For example, Kitwe, an urban mining site in Zambia’s copperbelt (estimated population of 12,000 in 1930) benefited from integrated malaria control, commencing in 1931 and sustained for two decades. Extensive water management, (e.g., drainage of swamps, river boundary modifications) and larviciding, together with house screening, use of bed nets and quinine administration to parts of the population were the mainstay of control.36– 38 The total costs for integrated malaria control measures at Kitwe and three other Zambian copper mining sites over a period of 20 years were US$ 11 million (expressed in 1995 US$). The interventions averted an estimated 14,122 deaths and an estimated 517,284 malaria attacks.38
Until World War II, integrated malaria control programs with strong emphasis on environmental management were successfully used in many malaria-endemic areas. Unfortunately, these approaches virtually disappeared during the global malaria eradication campaign in the 1950s and 1960s, which heavily relied on DDT. Environmental concerns, the high costs of repeated application of insecticides, and the development and rapid spread of insecticide resistance have stimulated renewed consideration of environmental management within integrated control operations.39 Urban settings are particularly appealing because of the focal and heterogeneous nature of malaria transmission.12, 40 Recently developed malaria transmission models provide further evidence that integrated control approaches, with multiple interventions implemented simultaneously, are crucial for successful malaria control because they suggest drastic reductions in EIRs. They can also reduce malaria transmission by factors of 15–25, which is enough to alleviate mortality.41, 42
Currently, malaria control in urban African settings consist mainly of early diagnosis and prompt treatment, and the promotion of ITNs. We propose to strengthen these programs and include environmental management as a key feature for sustainable mitigation of the burden of malaria in urban Africa. Interventions that consider the different facets of the urban environment have the potential to be broadly applicable and affect the health of many inhabitants.43
To provide effective and sustainable malaria control to the urban population of Africa will require massive commitment at national and international levels. Operational constraints such as supply, delivery, or logistics have to be carefully considered to secure long-lasting effective malaria control programs. Private-public partnerships, strategic investments in capacity building, training of national professional and auxiliary staff, health education of the community, and participation are equally important parts of successful integrated control programs. Careful planning in the design and implementation of interventions is paramount since environmental risk factors and malaria transmission depend upon locality. Furthermore, a sound knowledge base of the bionomics of the key malaria vectors and ongoing monitoring of breeding sites and their changes over time is of pressing necessity for the implementation of readily adapted environmental management interventions. Disease risk mapping produced with high spatial resolution imagery can provide an initial basis for identifying and analyzing the determinants of malaria risk, which has been demonstrated in an urban malaria control program in Dar es Salaam between 1988 and 1996.44 Pursuing this approach will also ensure that particular attention is paid to highly vulnerable and most disadvantaged urban environments, where the risk of disease-associated morbidity and mortality is highest, and where people are in most need.
In-depth studies are currently underway in the cities of Abidjan (Côte d’Ivoire), Cotonou (Benin), Dar es Salaam (Tanzania), Douala (Cameroon), and Ouagadougou (Burkina Faso) to develop and validate new approaches for rapid appraisal of malaria risk. These studies will facilitate the development and implementation of sound malaria control that will be of relevance for the entire sub-Saharan Africa.
We thank Dr. G. F. Killeen for his helpful comments on the manuscript and Nafomon Sogoba for access to data summaries from the MARA database.
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Received August 21, 2003.Accepted for publication November 15, 2003.Reprint requests: Jennifer Keiser, Swiss Tropical Institute, PO Box, CH-4002, Basel, Switzerland, Telephone: 41-61-225-2666, E-mail: Jennifer.Keiser@unibas.ch.
Financial support: This work was supported by the Center for Health and Wellbeing at Princeton University (Jürg Utzinger and Marcia Caldas de Castro), the Office of Population Research (Marcia Caldas de Castro), and the Swiss Tropical Institute (Jürg Utzinger).
Authors’ addresses: Jennifer Keiser, Jürg Utzinger, Marcia Caldas de Castro, and Burton H. Singer: Office of Population Research, Wallace Hall, Princeton University, Princeton, NJ 08544, Telephone: 609-258-6965, Fax: 609-258-1039. Thomas A. Smith and Marcel Tanner, Swiss Tropical Institute, PO Box, 4002 Basel, Switzerland, Telephone: 41-61-284-8273, Fax: 41-61-271-7951.
Jennifer Keiser, Jürg Utzinger, Marcia Caldas De Castro, Thomas A. Smith, Marcel Tanner, and Burton H. Singer.
American Society of Tropical Medicine and Hygiene, Northbrook (IL)
Keiser J, Utzinger J, De Castro MC, et al. Urbanization in Sub-Saharan Africa and Implication for Malaria Control. In: Breman JG, Alilio MS, Mills A, editors. The Intolerable Burden of Malaria II: What's New, What's Needed: Supplement to Volume 71(2) of the American Journal of Tropical Medicine and Hygiene. Northbrook (IL): American Society of Tropical Medicine and Hygiene; 2004 Aug.