Rapid urban malaria appraisal (RUMA) in sub-Saharan Africa
Rapid urban malaria appraisal (RUMA) in sub-Saharan Africa
Shr-Jie Wang 2
Christian Lengeler 2
Thomas A Smith 2
Penelope Vounatsou 2
Guladio Ciss 1
Diadie A Diallo 0
Martin Akogbeto 5
Deo Mtasiwa 4
Awash Teklehaimanot 3
Marcel Tanner 2
0 Centre National de Recherche et de Formation sur le Paludisme , (CNRFP) 01 B.P. 2208, Ouagadougou 01 , Burkina Faso
1 Centre Suisse de Recherches Scientifiques (CSRS) , 01 B.P. 1303 Abidjan, 01 Cote d'Ivoire
2 Swiss Tropical Institute (STI) , P.O. Box, CH-4002 Basel , Switzerland
3 The Earth Institute at Columbia University , 215 West 125th St Suite 301, New York NY, 10027 , USA
4 Regional/City Medical Office of Health , P.O. Box 9084, Dar es Salaam , Tanzania
5 Centre de Recherche Entomologique de Cotonou (CREC), Ministere de la Sante Publique , B. P. 06-2604, Cotonou , Benin
Background: The rapid urban malaria appraisal (RUMA) methodology aims to provide a costeffective tool to conduct rapid assessments of the malaria situation in urban sub-Saharan Africa and to improve the understanding of urban malaria epidemiology. Methods: This work was done in Yopougon municipality (Abidjan), Cotonou, Dar es Salaam and Ouagadougou. The study design consists of six components: 1) a literature review, 2) the collection of available health statistics, 3) a risk mapping, 4) school parasitaemia surveys, 5) health facilitybased surveys and 6) a brief description of the health care system. These formed the basis of a multi-country evaluation of RUMA's feasibility, consistency and usefulness. Results: A substantial amount of literature (including unpublished theses and statistics) was found at each site, providing a good overview of the malaria situation. School and health facility-based surveys provided an overview of local endemicity and the overall malaria burden in different city areas. This helped to identify important problems for in-depth assessment, especially the extent to which malaria is over-diagnosed in health facilities. Mapping health facilities and breeding sites allowed the visualization of the complex interplay between population characteristics, health services and malaria risk. However, the latter task was very time-consuming and required special expertise. RUMA is inexpensive, costing around 8,500-13,000 USD for a six to ten-week period. Conclusion: RUMA was successfully implemented in four urban areas with different endemicity and proved to be a cost-effective first approach to study the features of urban malaria and provide an evidence basis for planning control measures.
Urbanization has a significant impact on the economy,
lifestyles, ecosystems and disease patterns, including
malaria [1,2]. An estimated 39% of the population in
subSaharan Africa (SSA) lived in urban areas in 2003 , 198
million Africans lived in urban malaria-endemic areas
and 24103 million clinical attacks occur annually in
those areas . An important message addressed in the
Pretoria Statement on urban malaria was that the malaria
control strategies used in rural areas cannot be directly
transferred to the urban context . The epidemiology of
urban malaria poses a number of specific challenges: i)
the first malaria infection occurs often late in childhood
and the acquisition of semi-immunity is delayed ; ii)
the intensity of the malaria risk is often heterogeneous
over small distances, being subjected to the degree of
urbanization of particular subdivisions [7,8] and their
proximity to possible vector breeding sites [9,10]; iii)
rural-urban migration is likely to increase the endemicity
of malaria ; iv) agricultural and animal husbandry are
important economic activities which create a favourable
environment for Anopheles breeding [12,13]; v)
marginalized populations usually lack access to health care, which
hampers the effectiveness of case management and the
promotion of intermittent antimalarials during
pregnancy [5,14-16]. There is now substantial private sector
activity in health care provision in many cities. The private
services providers are often untrained or unlicensed, but
are seen as a source of inexpensive care by patients. There
is not much information about the impact of the private
sector on case management.
Around 235 papers related to malaria epidemiology in
SSA urban settings were published from 1945 to 2004.
Entomological profiles and clinical patterns are known to
vary between urban, suburban and rural environments
. A review of other studies in SSA urban centres
showed that transmission patterns vary greatly by city,
season and age group. The overall prevalence of
parasitaemia was 4.0% in schoolchildren in Brazzaville , 2.4
10.3% in Lusaka , 2.0% in a Gambian urban area 
and 3.67.5% in Dakar . It was also reported that
malaria prevalence in school children varied from 3.0% to
26.4% in different areas of Ouagadougou  and varied
from 14% in a central urban area to 65% in peri-urban
areas in Kinshasa .
Evidence showed that the rate of clinical malaria attacks
detected in urban health facilities was high and
seasondependent. For example, Hendrickse et al. found that
36.8% of outpatients were parasitaemic in a hospital in
Ibadan . In Niamey, the parasite prevalence was
61.9% during the rainy season but only 5.4% in the dry
season in 1989 . In Kinshasa, malaria admissions
comprised 29.5% of consultations in 1983, then 38.2% in
198586 . In Dakar, malaria fever represented 19.7%
of consultations and 34.3% of fever cases were caused by
malaria in 1988 ; the same authors found that 5.3%
(dry season) and 58.8% (rainy season) of febrile
outpatients were parasitaemic in 1994 . In Ouagadougou,
malaria prevalence accounted for 33% of all outpatients
, while Dabire reported 22% malaria parasitaemia
among children aged 014 years in the paediatric ward
Transmission and severity of malaria are influenced by the
geographic characteristics of a town and by the
socio-economic environment. The heterogeneity and seasonal
variation of the entomological inoculation rate, depending
on both vector densities and sporozoite rates, have been
documented [31,32]. Lindsay et al. (1990) showed a
difference in the composition of vector species and the
vector's adaptation in different subdivisions Banjul . To
improve interventions, the determinants of the diversity
of transmission levels within subdivisions of a city should
be understood. Concerns were raised about the
association between urban agricultural activities or local
irrigation systems and the creation of breeding sites for
Anopheles sp. [12,33,34]. Peri-urban areas often lack
infrastructure, including poor water supply and sanitation,
which provides an ideal environment for vector breeding
. For example, urban Dakar has >5,000 market-garden
wells which provide permanent sites for mosquito larvae
. An identification of vector species, regular larval
inspection and larviciding activities should be
implemented in the framework of urban malaria control
This article presents the experience of developing a rapid
urban malaria appraisal (RUMA) in SSA, carried out with
the support of the Roll Back Malaria Partnership. The aims
were i) to develop a rapid assessment package that is
explicitly evidence-based and can be carried out within a
six to ten weeks timeframe; and ii) to assess how rapid
malaria appraisal efforts could be best integrated into the
municipal health department supervision and to inform
The fieldwork took place in Yopougon municipality/
Abidjan (Cte d'Ivoire), Ouagadougou (Burkina Faso),
Cotonou (Benin) and Dar es Salaam (United Republic of
Tanzania) (Figure 1).
Abidjan is the economic capital of Cte d'Ivoire. It is
located between latitude 3.7 N4.0 N and longitude
5.7 E6.0 E, with a surface area of 454 sq. km. The study
was carried out in the large commune of Yopougon
(population: 775,000 in 1998) located in the west of
FMiagpuorefm1ajor urban areas in sub-Sahara Africa and the four selected project sites
Map of major urban areas in sub-Sahara Africa and the four selected project sites. Major cities (=M) and population density
(red >=200, green > 100 and blue = 40 population per square kilometres. Copyright: MARA/ARMA.
Abidjan . The fieldwork in Yopougon municipality
(Abidjan) took place from August to September 2002.
Ouagadougou, the capital of Burkina Faso, is situated on
the Sahelian border between latitude 12.0 N13.0 N
and longitude 1.15 E1.40 E. The total surface area was
estimated to be around 570655 sq. km in the year 2000
. The population of Ouagadougou was around
1,100,000 inhabitants in 2002. The fieldwork in
Ouagadougou took place from November to December 2002.
Cotonou is the economic capital of Benin. It is located on
a strip of land between Lake Nokou and the Gulf of
Guinea (between latitude 6.2 N6.3 N and longitude
2.2 E2.3 E). The total population was estimated at
780,000 inhabitants on a territory of 73.8 sq. km in 2002
. The fieldwork in Cotonou took place from February
to March, 2003.
Dar es Salaam is situated between latitude 6.0 S7.5 S
and longitude 39.0 E39.6 E on the East African coast.
There are 2,500,000 inhabitants on a total surface area of
1. Literature x
2. Collection x of health statistics
5. Health x
6. Brief description of the health care system
1,393 sq. km . The fieldwork in Dar es Salaam took
place from June to August, 2003.
health system information and statistics, including
routine malaria morbidity and mortality reports.
In July 2002, a generic RUMA protocol was developed
based on existing urban malaria research protocols
[41,42]. The relevant institutions in each setting were
contacted and city-specific proposals were then produced.
Parts of health facilities mapping, school and health
facility-based survey activities were integrated into the routine
surveillance and health system evaluation at the
municipal level. All the fieldwork was completed in August 2003.
Final reports were completed in June, 2004.
The six key components of the RUMA were the following
(see also Table 1):
1. Literature review. A search of the PUBMED biblio
graphic database was conducted for the time period from
1960 to April 2004, using the terms "malaria", "urban"
and "sub-Saharan Africa". The search was limited to the
articles published in English, Chinese, French and
Spanish. The reference list of all identified papers was screened.
Thesis abstracts filed in the medical libraries of
universities and national hospitals were collected at each site and
local researchers were also contacted.
2. Collection of routine health statistics. Local experts in
ministries of health (MOH) (disease surveillance systems,
municipal health departments and national malaria
control programmes) and national census and statistics
bureaus were contacted to collect demographic data,
3. Mapping of health care facilities and major Anopheles
breeding sites. Three or four trained workers carried out
the health facility mapping under the guidance of local
health personnel. In order to identify Anopheles breeding
sites, simple larvae sampling was performed with the
assistance of entomological technicians in Dar es Salaam
and Ouagadougou. The duration of these tasks varied by
site: 12 weeks during the rainy season in Dar es Salaam
and around three weeks during the dry season in
Ouagadougou. Due to security issues and technical problems,
the mapping of breeding sites and health facilities could
not be performed in Yopougon municipality (Abidjan)
4. School parasitaemia surveys. School surveys were
aimed at determining the local endemicity and risk
gradient of malaria. In each city, three to four schools with
different malaria endemicity (centre/low, intermediate/
medium and periphery/high) were investigated. It is a
rapid assessment with limited budget; therefore, in each
area only one health facility and school were selected for
the surveys. The schools were selected near the selected
clinics. 200 school children aged 610 years were
recruited in each school. Additional information on
children was collected using a questionnaire with the
assistance of teachers (see Additional file 1).
5. Health facility-based surveys (See Additional file 2). The facility-based fever surveys focused on the age-specific
fraction of malaria-attributable fevers . Each city was
categorised into three to four areas (centre, intermediate,
periphery and rural areas) and one clinic from each area
was chosen. Health facilities with a high enough volume
of outpatients per day were considered for the survey. In
urban areas, an estimated 5% to 50% of fever cases among
children under 15 years old were due to malaria. A sample
size of 200 in each facility gave an estimate of the
proportion of cases with parasites with the following
approximate lower 95% confidence limits (at 5%, lower 95% CI:
2; at 50%, lower 95% CI: 6). In each clinic, 200 fever cases
and 200 non-fever controls were recruited, with half of
them being aged <5 years. Outpatients with a history of
fever (past 36 hours) or a measured temperature 37.5C
were defined as cases. Controls were recruited from
another department of the same clinic without current or
recent past fever, matched by age and residency.
Electronic thermometers were used to measure the armpit
temperature. A "normal" body temperature is referred to
as an oral temperature of 37C. An armpit temperature
reading is usually 0.3C to 0.6C lower than an oral
temperature reading. Therefore 0.5C was added to the
temperature displayed on the digital readout. Thick and thin
blood films were taken to identify malaria infections.
Using 100 magnification to read the thick smears, all
malaria trophozoites and gametocytes were counted
separately. Parasite density was calculated according to
parasites per 200 white blood cells in a thick film (assuming
8000 white blood cells per ml of blood). If 200 white
blood cells were counted and less than 9 malarial
parasites found, the counting continued until 500 white blood
cells were identified.
6. Brief description of the health care system. It focused on i) the municipal malaria control and prevention efforts,
ii) the levels and coverage of service delivery, iii) disease
surveillance systems, iv) malaria case management and v)
trends of parasite resistance to antimalarials.
Quality assurance for blood slides
The diagnostic performance and the quality of blood
sample readings were checked twice: first in the field and then
at the reference laboratory of the Swiss Tropical Institute
(STI) in Basel, Switzerland. The results in Yopougon
municipality (Abidjan), Dar es Salaam and Ouagadougou
were: sensitivity 87.9%, 83.5% and 98.7%; specificity
89.2%, 99.0% and 98.2%; accuracy rate of slide readings
88.8%, 98.5% and 98.6%. The quality control process was
not implemented in Cotonou due to operational
The financial cost of the resources required for a RUMA
were calculated for each site based on local market prices
and salary standards, except for the laboratory material
that was purchased in Switzerland. All expenses fell into
seven categories: salaries, transportation,
communications, stationery, laboratory materials, other cost and
administrative fees (Table 2). A project team was
assembled within the existing structure of partner institutions
and then the accountants in each site used a
setting-specific cost model to identify the cost factors and determine
their local value. The preparation and training cost,
programme and administrative costs with the partner
institution were estimated and an allowance was added for
unforeseen circumstances in the finalized budget. The cost
for resources like microscopes and drugs for treatment,
vehicles and computers were calculated according to the
cost structure of the host institution.
Gross salary Salary slips or personnel records
Per diem from the project office
Petrol and maintenance of vehicles Bills and receipts
based on vehicle logbook Tickets and receipts Invoices
Actual expenditure Freight cost
Actual expenditure for items
International trade good price
Bills and receipts
Agreement with site
Collection of health statistics
Cross-sectional mapping of healthcare facilities
& major Anopheles breeding sites
School parasitaemia surveys
Health facility-based fever surveys
Brief description of the health care system
Good description of malaria burden over a
longer time period
Incomplete information in time and space
Completeness and quality of data
Visualization of information for policy makers Time consuming and only limited scale
Helps to plan urban health programmes and possible
upgrade community infrastructure Breeding sites may be transient /seasonal
Estimates malaria-attributable fevers and
prevalence of clinical malaria
Description of fever management
Limited representativeness if only small
number of schools were sampled
Only focuses on the available information
Depends on the efficiency of information
dissemination within municipal departments
One of the principal aims of the present work was to
review the feasibility, perceived usefulness and
consistency of the collected information. Because RUMA was a
cross-sectional assessment the external validity of the
findings could not be assessed. However, the internal
consistency of the results was assessed.
Below, the strengths and weaknesses of each
methodology are presented, bearing in mind the constraints
imposed by a rapid assessment. Detailed results for each
site will be provided in a series of forthcoming
Literature review (Tables 1 and 3)
The systematic review of all literature in each city allowed
the collection of background information in a
time-efficient manner. A substantial body of information was
found in each setting, although it was often incomplete in
place (for example covering only a part of the city), in
time (few time points, only one season) and in content
(not all subject areas covered). For the period 1945 to
2004, a total of 109 papers was found (18, 23, 29 and 39
for Abidjan, coastal Benin, Dar es Salaam and
Ouagadougou, respectively), relating to malaria epidemiology,
socio-economic risk factors of malaria, entomology and
drug resistance .
Collection of health statistics (Tables 1, 3 and 4)
The routine weekly or monthly malaria reports provided
a baseline on the burden of malaria in public health
facilities, as well as an assessment of the scale of malaria
treatment. Overall, case detection in the antenatal clinics and
public health services was poor and reporting was not
systematic and consistent.
In Abidjan, data were collected from the national malaria
control programme (Table 4a). Age-specific monthly data
were available. The statistics for 2001 from four out of 10
communes were missing. The malaria cases reported from
the main hospitals (Centre Hospitalier
UniversitaireCHU) in Yopougon, CHU Cocody and CHU Treichville
were separated from the commune data. CHU receive
many referral patients and the malaria cases may therefore
be over-reported. The data from CHU Yopougon were
missing for 2001.
a) Abidjan 2001
c) Dar es Salaam 2000 Total 178,016 d) Cotonou 2002 Kossodo
Reported number of malaria cases divided by the total number of consultations.
Both Ilala and Temeke district hospitals have malaria reported weekly and monthly. The raw dataset of malaria reports of district hospitals in
Kinondoni was missing in 2001. Total numbers of consultations were estimated.
In Ouagadougou, the number of malaria-specific cases
and the total number of consultations were collected. The
raw data were available by season for 19992001, but not
for 2002. All the data were missing for Paul VI sanitary
district from October to December 2001. The reporting of
clinical malaria was also inconsistent in Paul VI (Table
In Dar es Salaam, the weekly malaria reports were
collected from the Ilala, Kinondoni and Temeke district
health departments. The data were available for 2000-mid
2003, two months before the survey. A discrepancy in
records in Kinondoni District was found, as not all health
facilities sent their weekly reports to the district municipal
office. Moreover, the sums of reported malaria cases in the
raw dataset and in the final district reports were not
identical. The Kinondoni district health department had lost
all of its 2001 weekly reports (Table 4c).
Only Cotonou had complete data sets for 19962002, but
the raw datasets were unavailable. Hence, it was
impossible to review the consistency and accuracy of the data
Overall, considerable gaps were found in the routine
surveillance systems, particularly for remote health services.
Often, the data were collected and presented in different
formats, making a generalization impossible and this
limited their usefulness. Furthermore, the municipal health
departments simply summed up the total numbers of
reported cases as they lacked the capacity to analyse these
data and to extract useful information for management
Mapping activities (Tables 1 and 3)
As stated above, the mapping activities were only done in
Ouagadougou and Dar es Salaam.
a) Public and private health facilities
In Dar es Salaam, the list of existing public and private
health facilities was updated and their locations were
recorded by a geographic positioning system (GPS). In
Ouagadougou, the mapping of health facilities and
schools was done in 2002 by the Ecole Inter-Etats
d'Ingnieurs de l'Equipement Rural (EIER), Burkina Faso.
Both digital city maps were updated and available for
b) Anopheles breeding sites
The malaria risks in Dar es Salaam and Ouagadougou
were displayed in relation to the location of health
facilities and schools. The mapping of Anopheles breeding sites
in Dar es Salaam was done on a city wide-scale in
conjunction with another project [36,45]. In Ouagadougou, in the
limited time available, the focus was on permanent and
semi-permanent breeding sites instead of searching for
the numerous temporary breeding sites. The produced
maps of breeding sites indicated mosquito productivity
and distribution in the city in a given season.
The major drawback of mapping is that ground-truthing is
very time-consuming and variable over time. During the
rainy season, the city-wide larvae collection, larvae
hatching and management of data are difficult tasks. Another
disadvantage of this approach is that it tends to be very
expensive, unless local Geographic Information Systems
(GIS) mapping expertise and/or digital city maps are
already available for public use. For future studies, it is
recommended focusing on the mapping of health facilities
and dropping the breeding sites work as it is difficult to
assemble a team with the required expertise within such a
short time period.
School parasitaemia surveys (Tables 1 and 3)
It was possible to determine the transmission intensity
and gradients in different communities. At each site,
parasitaemia and fever prevalence rates were obtained for
different schools (Figures 2a, 2b, 2c) and by residential areas
of children. Around 10 to 70% of children (from city
centre to periphery) attended schools with elevated
temperature. Malaria prevalence was always higher than
the fever prevalence in Ouagadougou since there were
many asymptomatic infections. Different communities in
Ouagadougou may be exposed to different patterns of
malaria transmission and hence the age at first infection
and infection patterns may vary. Certainly, the more
exposed areas of Ouagadougou experience hyperendemic
(if seasonal) malaria. The association between malaria
infections and various risk factors were measured and
these results are reported elsewhere [46-49].
Health facility-based surveys (Tables 1, 3 and 5)
Both the fever and control groups (non-febrile admission)
had a medium level of parasitaemia prevalence in the
health facilities in Yopougon municipality (Abidjan) and
Ouagadougou (Table 5). Some people in the control
groups reported self-medication with paracetamol or
traditional herbs before visiting the clinics. This could have
led some malaria cases to present without fever at the
clinic. The overall prevalence of malaria was surprising
low in Cotonou and Dar es Salaam. This might have been
due to high Insecticide Treated Nets (ITNs) coverage and/
or the dry climate at the time of survey [46-49].
The detection of malaria parasites in a febrile case does
not necessarily indicate clinical malaria. In an effort to
improve the case definition and clinical diagnosis, the
method of Smith et al.  was used to estimate the
probabilities that individual episodes were really due to a
malaria infection. The odds ratio (OR) is the proportion
of odds of having parasitaemia in fever cases over
controls. The formula for the fraction of fever episodes
attributable to malaria parasites is: (1-1/Odds Ratio)*P. P is the
proportion of fever episodes in which the subjects had
parasitaemia. These age-specific malaria attributable
fractions were very low: 0.120.27, 00.04, 00.02 and 0
0.13 in Yopougon municipality (Abidjan), Benin, Dar es
Salaam and Ouagadougou, respectively. These results
indicated substantial over-treatment at all sites [46-49].
The questionnaires (available as a separate file)
administered to cases and controls were tailored for local use.
They contained four sections: personal information,
economic situation of the family, travelling history,
clinical signs and malaria history. The information on age, sex,
measured axillary temperature, length of febrile illness,
types of previous treatment and the reasons for seeking
care were obtained. Stay outside the urban area during the
previous three months, the type of housing, urban
agriculture activities and ITNs usage were also investigated. These
data provided indications of disease perception,
preventive measures and socio-economic background at
The questionnaires administered to cases and controls in
health facilities were similar to the ones used in school
surveys. In all settings the two sets of data were
comparable, which allowed for an internal consistency check. For
example, in Dar es Salaam 43.1% and 40.2% of
households reported ITN use in both the health facility surveys
and the school parasitaemia surveys. In Cotonou, these
figures were 36.6% and 28.4%, in Ouagadougou 7.8%
and 11.1%. The similarity of both surveys also made
possible a combined planning and implementation strategy.
Detailed results are presented elsewhere [46-49], as well as
in a series of forthcoming publications.
Brief description of the health care system (Tables 1 and 3)
The administrative structures of the national and
municipal health departments were sketched out and the list of
health facilities was updated at each site. The total
numbers of registered malaria diagnosis or treatment providers
were: 1060 in Abidjan, 365 in Cotonou, 1684 in Dar es
Salaam and 315 in Ouagadougou. Non-governmental
organizations and religious hospitals play an important
role in health care delivery in Cotonou and
Ouagadougou. The catchment areas of all public and
private health facilities were further calculated [46-49]. The
city malaria control programmes and WHO offices
PFrigevuarlen2ces of parasitaemia and fever detected in schools, in three sites
Prevalences of parasitaemia and fever detected in schools, in three sites. The vertical bars represent the 95% CI. a)
Ouagadougou. b) Dar es Salaam. c) Cotonou
Malaria Fever 73.1% 31.6%
Intermediate Kossodo A, B, C Periphery
Intermediate Periphery Rural areas
Children 15 years
Children 615 years
Adults >15 years
vided information about current malaria control efforts.
In order to assess treatment efficacy, the trend of the
susceptibility of P. falciparum to different antimalarials was
reviewed at each site [46-49].
This component required few resources and brought
strong political commitment because it involved
representatives of the Ministry of Health and the Directors of
the municipal health department. The extra-budgetary
resources from RUMA helped the local governments to
better monitor the provision of health care services, which
facilitated an effective exchange of information. The
health information was updated but the quality of health
care delivery was not assessed because of restricted scope
and time. The disadvantage of this approach is that
effective communication and dissemination of official
documents depends on the attitude of senior officers.
Compared costing of RUMA activities
The cost for conducting a RUMA in a SSA city with a
population of 0.53 million is around 8,50013,000 USD for
a six to ten-week period (Table 6). The cost of human
resources in Dar es Salaam and Ouagadougou was
highest, mainly because of the additional fieldwork performed
there (mapping of breeding sites and health facilities).
Indeed, the per diem standard was lower in these cities.
The higher savings on transportation, communications
and materials in Abidjan and Ouagadougou were made
possible by our affiliation with local research institutions.
The total expense in Abidjan was much lower because the
school survey was not performed (the children did not
attend school during a politically troubled time). In
Cotonou, the excess of human resource and
transportation cost was due to unforeseen supervisory expenses.
In general, the difference in the cost of human resources
and communications was due to differences in personnel
capacity and fluctuations in the amount of work. The costs
of stationery and laboratory materials were less variable,
because the needs were the same at each site.
Discussion and conclusion
This assessment was accomplished in four countries
within a period of six to ten weeks in the field and has
proven to be a helpful tool in supporting planning of
urban malaria control. An ongoing urban malaria control
intervention in Dar es Salaam has been initiated on the
knowledge basis provided by RUMA. With the incentive
of extra-budgetary resources and technical support from
STI, local partners were committed to incorporate RUMA
into existing activities at the municipal level. Qualified
personnel and opportunities for integration, synergy and
co-ordination were identified during the meetings with
local partners and the collaborations were always very
The RUMA methodology is a cross-sectional design and
the results are likely to change over time due to
seasonality, the dynamics of urbanization and the evolution of
malaria transmission. In Dar es Salaam, for example, the
surveys were carried out during an exceptionally dry
period and results could underestimate the true
transmission intensity. Many factors such as the size of the city, the
fieldwork logistics, the availability of local expertise and
the coordination with local senior officers can influence
the schedule and planning, as well as the outcome of such
The study highlighted the need for improved Health
Management Information Systems (HMIS) in SSA urban areas.
Municipal health departments routinely collect health
facility data but information is rarely fed back to the
districts and facilities that generate the information. The data
are often not available for analysis or accessible due to
false registration and under-reporting from health
facilities, as well as poor filing and storage of documents at the
district or municipal level. In addition, the low number of
without GIS mapping and 1st quality control without GIS mapping and school survey
* with second quality control at Swiss Tropical Institute.
the second quality control was free
true malaria cases among fever episodes treated as
"malaria" raises the issue of the validity of the collected
data even further. Hence, much progress needs to be made
in order to estimate more accurately the urban malaria
burden and plan relevant control measures.
GIS provides a platform to display health services and
geographic features in relation to population settlements.
In this experience policy-makers could readily use the
presented information for improved planning, re-allocation
of resources and for strengthening the networking
between the public and private sectors. While the GIS
technology has been shown to be very useful in studying
health care delivery and distribution of diseases, its
application in an entomological assessment was quite difficult
and costly and could only be done in conjunction with
other ongoing projects. Hence it should be excluded from
the process of RUMA. In contrast, the mapping of health
facilities with GIS was feasible and cost-effective.
While results from the school surveys gave an indication
of the endemicity range and risks in the targeted
community, they cannot be considered as being representative
without a wider survey. The variations of malaria risk were
sometimes related to political divisions or man-made
boundaries, but often were due to divergent
socio-environmental factors and the degree of urbanization. Because
site-specific environmental conditions lead to an
aggregated distribution of vectors and different malaria risks,
the sampling sites were selected taking into account the
population density, the natural environment and
urbanization patterns. This should improve the rough categories
that previous researchers applied (centre, intermediate
Despite a potential attendance bias, the health facility
surveys allowed the determination of prevalence of
parasitaemia among presenting clinical cases, and the calculation
of the fraction of malaria-attributable fevers. This allowed
to document clearly the high rate of malaria mis-diagnosis
in the health facilities. This information is of great
importance for urban malaria control.
Overall, RUMA is a first step towards understanding
malaria endemicity and designing control strategies. It has
exemplified the concern for mis-diagnosis of clinical
malaria in SSA cities [25,50]. A report by the
TanzaniaJapan malaria control programme in Dar es Salaam
mentioned that drug administration to diagnosed children
was one of the essential interventions that reduced the
malaria rates between 1988 and 1996 . An in-depth
research is now being implemented in Dar es Salaam to
assess the malaria burden with a much larger sample size.
The application of RUMA methodology is possible and
desirable in other SSA urban areas and it should have a
special focus on improved diagnosis.
List of abbreviations
CHU Centre Hospitalier Universitaire
CNRFP Centre National de Recherche et de Formation sur
la Paludisme, Burkina Faso
CREC Centre de Recherche Entomologique de Cotonou
EIER Ecole Inter-Etats d'Ingnieurs et de l'Equipement
Rural, Burkina Faso
GIS Geographic Information System
HMIS Health Management Information Systems
ITNs Insecticide-Treated Nets
MOH Ministry of Health
RUMA Rapid Urban Malaria Appraisal
SSA Sub-Saharan Africa
STI Swiss Tropical Institute
SW participated in the design of the study, conducted the
field work, analysed and interpreted data and drafted the
manuscript. CL conceived the study, coordinated the field
work and revised the manuscript. TS and PV assisted in the
design and the statistic analysis. CG, DD, MA and DM
were the key local contacts, facilitated the collaboration
and supervised the data collection and laboratory works at
each site. AT participated in the design of the study. MT
participated in the conception of the work, facilitated the
overall coordination and revised it critically at all stages.
Additional File 1
Additional File 2
We would like to acknowledge the support and help of the following
institutions and persons. In Benin: Francois Holtz; in Burkina Faso: the Ecole
Inter-Etats d'Ingnieurs de l'Equipement Rural; in Cte d'Ivoire: Dr. Joseph
Niangue; in Tanzania: Ifakara Health Research and Development Centre.
We wish also to express our gratitude to Dr. Andrei Chirokolava for
editing and reviewing the city reports. RUMA was supported financially by the
Roll Back Malaria Partnership and STI.
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