de Castro, Marcia Caldas

Fillinger, Ulrike

Kalongolela, Martin S

Kannady, Khadija

Killeen, Gerry F

Lindsay, Steven W

Mukabana, W Richard

Tanner, Marcel

English

Digital Library of the Tanzania Health Community

LETTERS TO THE EDITOR
HABITAT TARGETING FOR CONTROLLING AQUATIC STAGES OF MALARIA
VECTORS IN AFRICA
The publication of several articles of immediate relevance in recent weeks has prompted the authors to revise this
letter immediately prior to publication. It was not possible to incorporate these changes at the proof stage so the revised
version is available at www.ajtmh.org.
Dear Sir:
Gu and Novak
1 have recently highlighted the potential for
improving the cost-effectiveness of mosquito larval control as
a malaria prevention measure in Africa, if the most produc-
tive habitats could be identified and targeted. We agree that
this is, in principle, a valid hypothesis that probably holds true
to some extent in real African field situations. However, we
do have three major reservations that have substantial impli-
cations for the development of operational mosquito control
programs in the poorest nations of tropical Africa. In the
absence of a contemporary evidence base for the application
of source reduction in Africa, we suggest the following cave-
ats should be considered as the operational research commu-
nity strives to translate the recent wave of historical review,
theoretical elucidation, and supporting field ecology studies
into sustainable, cost-effective programs that kill mosquitoes
and prevent malaria. We outline each concern in increasing
order of importance:
First, we suggest that their mathematical description under-
estimates the likely impact of untargeted control. Specifically,
we believe that equation 2 (described as S2 in their paper)
does not accurately represent the untargeted scenario it is
intended to. The authors acknowledge that many aspects of
the model have been adapted to represent conditions under
which the phenomenon in question is most obvious and im-
portant. The approach they endorse has been restricted to
settings of modest endemicity where targets for reducing
transmission intensity are less intimidating,
2,3 but we would
prefer to have seen a range of settings and underlying condi-
tions explored to put the frequency of these restricted condi-
tions into perspective. Furthermore, we believe the formula-
tion described in equation 2 exaggerates the advantage of
targeting at low coverage levels, even under the conditions of
modest endemicity specified in this paper. In an untargeted
scenario, all habitats should have an equal chance of being
covered if they are readily visible and accessible, as is usually
the case for Anopheles gambiae Giles but far less so for
Anopheles funestus Giles.
4–7 Thus, effective coverage should
be directly proportional to overall coverage, regardless of the
distribution of productivities, unless the number of produc-
tive habitats is so small that they are easy to miss at low
coverage. We suggest such concentration of productivity in a
handful of cryptic habitats is unlikely to be the case in many,
if not most, parts of Africa. We interpret equation 2 in the
formulation of Gu and Novak as representing an active bias
against treatment of productive habitats, resulting in a much
larger gap between effective coverage of targeted and untar-
geted scenarios at coverage levels less than 60%. Addition-
ally, the logistic function presented has two tunable param-
eters ( and ) that seem to have been set to arbitrary values
to provide a relationship that fits with the hypothesis proposed.
This equation could be tuned to provide a number of curves,
some of which could be related to this issue but most of which
cannot. Of particular concern is the fact that this equation will
not yield P  1 where C  0 nor P  0 where C  1 unless
discontinuously defined. Furthermore, we cannot reproduce
the relationship described for S2 in Figure 1 using the equa-
tion provided and parameter values listed, getting instead a
flat saturated line with values of 99.7% for all values of cov-
erage from 0% to 100%. Despite these criticisms, we accept
that equation 3, representing the targeted scenario (S3), is
useful and still makes the point that targeting would represent
an improvement on an untargeted scenario. We conclude that
the point the authors are making is theoretically valid, but
untargeted larviciding can be represented more accurately
and convincingly by the existing simple, linear form presented
in equation 1 of their paper, as previously described.
8
Our second concern relates to the interpretation of our
published work.
9,10 The major conclusion we reached in both
of these papers is that some heterogeneities of apparent pro-
ductivity do exist, but they are not sufficiently large or pre-
dictable enough to enable rational targeting. Furthermore,
distribution of habitats themselves is highly dynamic and rep-
resents a moving target, even without considering variations
in productivity. Meteorological fluctuations combine with un-
derlying hydrology and human activity to generate a con-
stantly changing array of potential habitats. This is particu-
larly true for notoriously opportunistic members of the An.
gambiae species complex, for whom the majority of habitats
are usually man-made, even in rural settings.
5,9–15 Thus, while
we agree in principle with the hypothesis presented by the
authors, we suggest that the magnitude of variation in pro-
ductivity between habitats remains poorly understood and
difficult to predict in real field situations. Despite our long
experience with sampling Anopheles larvae in a variety of
sites across Africa, we are unable to reach consensus about
what the most consistently productive habitat types are or
where we would look for them on a given day in a given
setting. Even if the research community could reach consen-
sus on where to direct interventions, we raise the question as
to whether this knowledge could be translated into success
under operational conditions.
Our third concern relates to the likely impact of targeting
specific habitats under programmatic conditions. We share
the expectation that ongoing trials of larval control across
Africa will prove that appropriate larvicides are efficacious in
the hands of specialized research teams under the conditions
of randomized control trials. Nevertheless, experience with a
range of public health interventions has highlighted the mas-
sive gap between proving efficacy and achieving effective-
ness.
16 By necessity, sustainable operational programs to be
Am. J. Trop. Med. Hyg., 74(4), 2006, pp. 517–518
Copyright © 2006 by The American Society of Tropical Medicine and Hygiene
517implemented at national scales in Africa will be predomi-
nantly staffed by personnel with minimal educational qualifi-
cations and modest remuneration, under very challenging cli-
matic conditions. We therefore envisage that translation of
presently debatable ecological subtleties into rational target-
ing will be extremely challenging. Furthermore, we have
found a variety of existing preconceptions in communities
throughout Africa about where mosquitoes originate from
and an enormous variation in perceptions of where best to
target between individuals within the same locality. We have
experienced that consideration of such perceptions in deci-
sions to apply larvicides results in inconsistent levels of cov-
erage and targeting. It also makes management of such pro-
grams, even on small scales, almost impossible because it al-
lows a range of reasons for not having treated a habitat,
making the “individualization of responsibility,” which Soper
himself emphasized,
6,17 very difficult to realize in practice.
The most historically successful campaigns against African
malaria vectors have all included exhaustive coverage with
larval control strategies.
6,7,17–21 One secret of success in these
endeavors, particularly the Brazilian and Egyptian cam-
paigns, was the simple and readily verifiable targets provided
to field workers at the sharp end of the mosquito control
spear: to kill all mosquitoes. This “shoot first, ask questions
later” philosophy may seem crude in the modern era, but its
success remains unrivaled, and to implement it today is a
challenge in itself. We therefore support the hypothesis of Gu
and Novak but urge caution in considering the merits of tar-
geting strategies under research and programmatic condi-
tions. Unambiguous criteria for targeting may need to be es-
tablished through consensus among the scientific community.
If this can be achieved, we conclude that these new tools
could be evaluated as system interventions by comparing with
comprehensive coverage through large-scale effectiveness tri-
als under programmatic conditions.
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GERRY F. KILLEEN
Ifakara Health Research and Development Centre
Box 53
Ifakara, United Republic of Tanzania
Department of Biological and Biomedical Sciences\
University of Durham
Durham DH1 3LE, United Kingdom
MARCEL TANNER
Department of Public Health and Epidemiology
Swiss Tropical Institute
Socinstrasse 57
Basel CH 4002, Switzerland
W. RICHARD MUKABANA
Department of Zoology
University of Nairobi
Box 30197-00100 GPO
Nairobi, Kenya
MARTIN S. KALONGOLELA
KHADIJA KANNADY
City Medical Office of Health
Dar es Salaam City Council
Box 63320
Dar es Salaam, United Republic of Tanzania
STEVEN W. LINDSAY
ULRIKE FILLINGER
Department of Biological and Biomedical Sciences
University of Durham
Durham DH1 3LE, United Kingdom
MARCIA CALDAS DE CASTRO
Department of Geography
Callcott, Room 125
Columbia, SC 29208
LETTERS TO THE EDITOR 518

African Highway: The Battle for Health in Central Africa.

Anopheles gambiae in Brazil:

Biology of Anopheles gambiae. Geneva: World Health Organization.

Characterization of potential larval habitats for Anopheles mosquitoes in relation to urban land-use in

Child mortality and malaria transmission intensity in Africa.

Efficacy and cost effectiveness of environmental management for malaria control.

Eradication of Anopheles gambiae from Brazil: lessons for malaria control in Africa?

Evaluation designs for adequacy, plausibility and probability of public health programme performance and impact.

Following in Soper’s footsteps: northeast Brazil 63 years after eradication of Anopheles gambiae.

Habitat characterization and spatial distribution of Anopheles sp. mosquito larvae in Dar es Salaam (Tanzania) during an extended dry period.

Habitat-based modeling of impacts of mosquito larval interventions on entomological inoculation rates, incidence and prevalence of malaria.

Malaria transmission in urban subSaharan Africa.

Occurrence and distribution of Anopheles (Diptera: Culicidae) larval habitats on land cover change sites in urban Kisumu and urban Malindi,

Rationalizing historical successes of malaria control in Africa in terms of mosquito resource availability management.

Species-eradication the eradication of Anopheles gambiae from Upper Egypt, 1942–1945. Bull World Health Organ 1: 309–353. GERRY F. KILLEEN Ifakara Health Research and Development Centre Box 53 Ifakara, United Republic of Tanzania

The Anophelinae of Africa South of the Sahara (Ethiopian Zoogeographical Region).

The economic payoffs of integrated malaria control in the Zambian copperbelt between

The entomological inoculation rate and Plasmodium falciparum infection in African children.

The practical importance of permanent and semi-permanent habitats for controlling aquatic stages of Anopheles gambiae sensu lato mosquitoes: operational observations from a rural town in Western Kenya.

The Rockefeller Foundation.

Urbanization in sub-Saharan Africa and implication for malaria control.

Habitat targeting for controlling aquatic stages of malaria vectors in Africa.

http://ihi.eprints.org/246/1/517.full.pdf

Habitat targeting for controlling aquatic stages of malaria vectors in Africa.

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