MALARIA ELIMINATION IN ZANZIBAR - Soper Strategies

around 10-15. In this scenario, the lower value of 10 is used. As
in the scenario predicting transmission with nets, it is assumed
that passive case detection can promptly identify and treat 50%
of all infections, and that importation is either 2 or 8 per 1000
people/yr.
Under these conditions, repeated simulations indicate that malaria
would rapidly reemerge in Zanzibar unless other interventions or
health system strengthening take the place of the nets. In this
scenario, we assume that reemergence has occurred when 50 new
infections are identified within two weeks. At this threshold, it
is assumed that drastic action would be required involving focal
IRS, larval control, and other measures. This “failure” point was
reached within 9-13 months, depending upon assumptions about
importation. Such timing is in line with rapid resurgence observed
historically in places with a high R 0, including twice previously
in Zanzibar. Clearly, additional interventions are required if nets
are to be scaled back. As with the nets scenario, simulations were
used to estimate the minimum fraction of cases identified and
promptly treated through passive case detection or the amount of
active case detection that would sustain elimination.
Passive Case Detection
The simulation was run repeatedly at different levels of passive
case detection to determine the level at which local transmission
could be reliably kept below the threshold defined by the WHO.
Results indicate that, without nets, the percent of cases that must
be identified to ensure second generation transmission does
not occur in two consecutive years is 97-98%, depending upon
importation assumptions.
Achieving near perfect infection detection and treatment is
not technically feasible. Even if 100% of individuals with
clinical disease sought treatment at a public health facility,
some infections would remain asymptomatic and thus not seek
treatment. Additionally, diagnostics in the health facility will
always have some error, meaning that some infections will be
misdiagnosed.
Active Case Detection
Alternatively, active case detection (ACD) could be implemented
in lieu of increases in passive case detection (or in addition to
smaller increases). The simulation was run repeatedly at different
levels of active case detection, keeping the fraction of infections
identified by passive case detection at 50%, to determine the
level at which local transmission could be reliably kept below the
threshold defined by the WHO (Figure 20).
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FIGURE 20: RELATIONSHIP BETWEEN SIMULATED ONWARD TRANSMIS-
SION AND ACD GIVEN 0% EFFECTIVE ITN COVERAGE
2ND GENERATION CASES PER 1000 PERSON-YRS
14
12
10
8
6
4
2
0
0 200 400 600 800 1000 1200
HOUSES INVESTIGATED AROUND EACH IDENTIFIED INFECTION
The green line indicates predictions for importation = 2/1000
while the blue line is for 8/1000; the dotted line indicates the
approximate threshold below which WHO criteria for prevention of
reintroduction are met.
Results indicate that ACD alone is insufficient to prevent
reemergence of malaria if no increases in passive case detection
are assumed. The required amount of ACD will decrease as
passive case detection increases, but at 50% detection, nearly
every house in the region must be investigated following each
case to maintain elimination.
Combined Interventions
Increasing both passive and active case detection may result in
making it technically feasible to withdraw net coverage while
still maintaining elimination. Additionally, it may be possible
to decrease importation through border screening. Mainland
Tanzania is currently engaging in a massive effort to scale-up
ITN and ACT coverage around the country, which may also
decrease importation rates.
The fraction of cases that can be identified by passive case
detection is a function of the percent of infections that cause
clinical disease, the percent of febrile individuals that seek
treatment in the public sector, and the fraction of those at public
facilities that are tested and treated for malaria. It may be possible
for Zanzibar to increase the fraction of febrile individuals seeking
treatment in public health facilities greatly over the course of
the decade; as discussed above, the current rate of increase in
the fraction of parents taking febrile children to public health
facilities could reach 90% by 2020. The fraction of infections
that have clinical disease will increase as malaria become rarer;
we assume that 90% of infections will be clinically apparent
in 10 years time. Finally, it is assumed that all fevers are tested
and treated accordingly, but that achieving greater than 95%
sensitivity in diagnosis is not possible. As such, under these
assumptions, passive case detection would identify 90% x 90% x
95% = 77% of infections in Zanzibar.
The estimates of importation used here of 2 or 8 per 1000 people/
yr may also be reduced over time using border screening or due to
reductions in transmission on the mainland. If border screening
can test 90% of individuals entering Zanzibar with a 90% accurate