MALARIA ELIMINATION IN ZANZIBAR - Soper Strategies
MALARIA ELIMINATION IN ZANZIBAR - Soper Strategies
MALARIA ELIMINATION IN ZANZIBAR - Soper Strategies
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DATA COLLECTION METHODS<br />
A robust surveillance system on Zanzibar will need to incorporate<br />
both passive and active approaches to detecting and reporting<br />
malaria cases. Passive and active case detection have been defined<br />
as follows (Teutsch and Churchill, 2000):<br />
�� Passive case detection–system where data are routinely<br />
received by a central health authority based on a set of rules/<br />
laws that require a healthcare provider or health facility to<br />
report certain diseases or conditions on an ongoing basis and<br />
at specific intervals (weekly, monthly, annually).<br />
�� Active case detection–system where data are regularly pursued<br />
by a central health authority at periodic intervals, often with the<br />
intent to validate the representativeness of a passive surveillance<br />
system. An active surveillance system will likely provide more<br />
complete reporting, and can identify asymptomatic individuals,<br />
but it is more labor intensive and thus more costly to operate as<br />
compared to passive case detection.<br />
There is relatively little central guidance on both of these<br />
approaches for malaria elimination. This lack exists because<br />
they are highly context dependent and must be adapted to each<br />
country and area.<br />
Passive Case Detection (PCD)<br />
A strong passive case detection system is the cornerstone of<br />
any approach to surveillance–if new malaria cases identified at<br />
health facilities are not being adequately reported and followed<br />
up, elimination will not be achieved. In Zanzibar, the passive<br />
case detection system will have to be substantially improved to<br />
ensure that a high proportion of infections are detected (both<br />
symptomatic and asymptomatic) and reported to the central level<br />
with the required speed (e.g., initially within 24 hours but once<br />
at or near zero local transmission as soon as possible). From the<br />
results of the simulations described in the Technical Feasibility<br />
Chapter we know that as long as preventive measures have an<br />
effective coverage of 75%:<br />
�� Between 70-80% of infections have to be promptly identified<br />
and treated for passive case detection alone to be sufficient to<br />
avoid second-generation infections.<br />
�� Passive case detection that identifies around 50% of all<br />
infections–a detection rate only slightly higher than the<br />
present day–will need to be complemented with active case<br />
detection that screens about 100 households neighboring<br />
each newly identified case.<br />
Achieving the required detection levels is influenced by a range of<br />
factors: the fraction of infections that will become symptomatic,<br />
the people’s health seeking behavior for fever, testing rates at<br />
the facility, and the sensitivity of the test used. The operational<br />
requirements for the surveillance system to achieve the above<br />
mentioned detection levels are described below.<br />
In addition, the Zanzibar MOHSW will need to strengthen the<br />
central units that record and analyze cases that are reported by<br />
increasing human resources, improving skills, and obtaining<br />
appropriate technology.<br />
2 | Operational Feasibility<br />
Current System<br />
There are currently two systems for passive detection of malaria<br />
cases on Zanzibar: the Health Management Information System<br />
(HMIS) and a vertical Malaria Early Epidemic Detection System<br />
(MEEDS) through sentinel sites (52 sites operational in 2009).<br />
The HMIS is managed by a specific unit in the MOHSW that<br />
was established in 2001 and strengthened through funding from<br />
DANIDA. The HMIS serves as the primary clinical services<br />
monitoring system for the MOHSW and fits within the larger<br />
context of health sector M&E efforts in Zanzibar. Data from<br />
peripheral facilities are collected by the HMIS focal point at the<br />
district level. Aggregated data are compiled at the district level<br />
and sent to the HMIS unit in the MOHSW.<br />
Malaria information collected as part of the HMIS is supposed<br />
to be reported quarterly through District Health Management<br />
Teams (DHMT) and provincial offices. The cases reported are<br />
both (parasitological) confirmed and non-confirmed based on<br />
clinical diagnosis and therefore include non-malarious fever<br />
cases. Although most facilities have diagnostic capacity (RDT<br />
and/or microscopy) and the results are supposed to be captured<br />
in the laboratory reports, the HMIS is currently not providing<br />
this information to the ZMCP. The following indicators are<br />
theoretically available through routine HMIS:<br />
�� Out Patient Department monthly malaria cases (both<br />
confirmed and non-confirmed)<br />
�� Laboratory data (total slides, positive films for malaria<br />
parasites, hemoglobin tests)<br />
�� Malaria and severe anemia admissions and deaths<br />
Unfortunately, the information collected through the HMIS<br />
system is not routinely passed on to the different control programs<br />
within the MOHSW. The ZMCP therefore decided to collect<br />
malaria data for their strategic planning using 6 health facilitybased<br />
sentinel surveillance sites (HFBSS). These sites are part of<br />
the normal HMIS and do not report different information as such.<br />
The main difference is that the HFBSS provide regular, timely,<br />
high-quality malaria-related laboratory, morbidity, and mortality<br />
data, an important pillar for the ZMCP strategic decision. The<br />
MEEDS (see below) now provides these data regularly, and the<br />
HFBSS will most probably be scaled down and even stopped in<br />
the near future.<br />
The second existing malaria surveillance system, malaria<br />
early epidemic detection system (MEEDS), is connected to<br />
a broader effort by the MOHSW to strengthen infectious<br />
disease surveillance. It is funded by PMI and uses mobile phone<br />
technology to provide weekly malaria data to a central server<br />
where they are automatically analyzed. It provides aggregate<br />
data (for under fives and over fives) on total number of patients<br />
seen at the facility, total numbers tested and numbers testing<br />
positive. The MEEDS is so far the only operational component<br />
of the planned Integrated Diseases Surveillance and Response<br />
(IDSR) that aims at providing health workers with additional<br />
epidemiological information on key diseases to assist in decisionmaking<br />
on and implementation of interventions As the MEEDS<br />
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