MALARIA ELIMINATION IN ZANZIBAR - Soper Strategies

to below 1% with IRS (Bhattarai et al., 2007). These low levels of
malaria prevalence in Zanzibar today suggest that elimination is
feasible, although it may be challenging to go the last mile.
History has demonstrated numerous times that regions with high
innate risk of malaria will see rapid resurgence of transmission if
control measures are weakened or removed. For example, after
Madagascar instituted a control program of DDT spraying and
case detection and treatment in the 1940s and ‘50s, malaria
was nearly absent from the highlands for many years. But when
control activities were halted in the late 1970s, an explosive
epidemic caused an estimated 40,000 deaths over five years
(Mouchet et al., 1998). There are numerous similar examples
from diverse environments and areas of the world. In contrast,
countries that have effectively sustained interventions have
successfully maintained a high level of control or elimination.
In sub-Saharan Africa, examples of such success include South
Africa (control) and Mauritius (elimination), both of which had
to adapt their programs when changing conditions led to modest
resurgence (Julvez et al., 1990; Mabaso et al., 2004).
Zanzibar itself has already experienced such resurgence. Malaria
in Zanzibar reached a previous low forty years ago at the end of
the GMEP. In June 1968, with prevalence reduced over 10-fold
in Unguja and 40-fold in Pemba, malaria had been reduced to
a “minor health problem” (Tavrow et al., 1988). The program
was then halted for “political and economic reasons,” a trend that
was occurring around the world due to disappointment that full
elimination had not been achieved. Without control measures,
the resurgence of malaria was rapid (Schwartz et al., 1997). A
survey conducted five years after the end of the program found
that prevalence had rebounded six-fold to 54% prevalence
in Unguja and 10% in Pemba (Minjas et al., 1988). Should
history repeat itself and the current control measures be relaxed,
it is certain that malaria in Zanzibar will once again return to
hyperendemic levels within a few years.
CURRENT TRANSMISSION RISK
Actual levels of malaria transmission in Zanzibar at a given time
depend upon not only the historic, or innate levels of malaria, but
also the levels of control activities that will decrease transmission
from that baseline. Malaria transmission can be measured in
several ways, but an extremely useful measure is the number of
human malaria cases resulting from each human malaria case,
called the basic reproductive number R0 (Box 1), pronounced
“R naught.” R0 measures transmission under the conditions that
maximize transmission–no control and no immunity. To define
transmission risk under different levels of control, we use the
controlled reproductive number, RC, which is the number of new
infections that will result from each infection at a certain level
of control activities. Understanding both R0 and RC is critically
important for elimination and post-elimination planning, telling
us what interventions are needed to get to zero transmission and
how fast new imported cases might develop into outbreaks.
Box 1
The basic reproductive number R 0
1 | Technical Feasibility
Zanzibar’s high innate level of malaria–that is, the level of
the disease that would naturally occur if all control measures
were removed–is determined by the presence of efficient
vectors, including Anopheles gambiae, appropriate climate,
geography, and socioeconomic environment for malaria
parasites to spread efficiently. Together, these factors produce
a high basic reproductive rate of malaria (R0)-the number of
new infections an infected person would generate if there
were no control measures in place.
The controlled reproductive number R C
The value of R C indicates the number of new infections
that each infected person will generate under a given level
of control activities. If that value is greater than one, malaria
levels are increasing, while if it is less than one, they are
decreasing. The current R C level in Zanzibar depends on
the effective coverage of control activities. For example, if
around 60% of the population is fully protected by LLINs or
IRS, RC will be approximately equal to one, while if 75% of
the population is protected, it will drop to about 0.5.
To put the historical trends in malaria endemicity into a context
that is useful for assessing the technical feasibility of elimination,
it is necessary to estimate R0 and RC. Estimates of R0 for malaria
are based on the prevalence of malaria in children aged 2-10 and a
mathematical model of malaria transmission (Smith et al., 2007).
Zanzibar’s past hyperendemic malaria, with prevalence of around
60%, corresponds to estimates of R0 around 100, but with wide
confidence limits that suggest it was greater than 30 but could
have been as high as a thousand. More recent data suggest that
prevalence remained around 35-40% even in the absence of a
formal control program. This lower (though still high) level of
innate malaria suggests that R0 had fallen to around 10 or 15.
R C is likely to depend upon a diversity of spatially varying
factors including coverage of interventions like bednets or IRS,
socioeconomic conditions, and urban development. As such,
current levels of malaria transmission are not homogenous
across Zanzibar (Figure 5). Survey data indicate that Central
and North B on Unguja and Micheweni in north Pemba
appear to have higher malaria risk than elsewhere. These three
districts also were three of the four districts with the lowest
percentages of individuals reporting sleeping under treated nets
in a 2007 ZMCP survey; all reported figures lower than 50%.
Determining the relative importance of other factors will require
regular and detailed data on interventions, socioeconomic
status, development, and parasite prevalence across Zanzibar.
Nevertheless, recent years of transmission data indicate that R C
is likely around one on average, and it is probably lower than
one across much of Zanzibar, particularly in the high population
context of Stone Town and in surrounding urban areas.
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