The HEAS thanks the Cap Haitien Health Network for sharing their data. Epidemic response is ongoing in the region, and is still experiencing high medical response grid strain. We assess the region to be representative of IDIS Cat 4, with evidence of occasional spikes to Cat 5 depending on the patient surge : availability of medical resources ratio.
This data highlights important patterns of the epidemic. Where we often see officials and media reports quoting national level statistics of the epidemic showing an ever-increasing trend, this data provides another view into the intense, highly localized transmission that has been seen. The general rule of thumb is the higher the number of fatalities in the smaller the geographic area, the greater the potential for massive social disruption and potential erosion of civil order.
The Cap Haitien Region continues to report increased cholera case counts along with increased fatalities. We are not seeing a peaking yet in case loads for the region.
The region includes the following sites that have reported cases:
- Cap Haitien
- Limbé
- Pilate
- Plaisance
- Bas Limbé
- Borgne
- Acul
- Saint Raphael
- Gde Rivière
- Port Margot
- Pignon
- Milot
- Bahon
The following displays the rank order, by location, for total case counts, fatalities, and case fatality rate-apparent (CFR-apparent). The term "apparent" is our acknowledgement there is substantial under-reporting owing to the fact that subclinical cholera is present in the community, rural areas experiencing cholera may not have submitted their statistics yet, among other factors that may prevent a fully accurate accounting for the region. "Apparent" therefore reflects the number of fatalities divided by the cases reported.
When considering the experience of each location, the site by site differences are impressive:
When considering the CFR-apparent on a daily basis, evidence of which site appeared to gain control of the situation through medical response sensitization, adaptation to crisis conditions, and access to adequate resources. In other words, previously inexperienced medical responders at a given site, upon first encounter with cholera are often taken by surprise. Although the degree of surprise is lessened by prior warning, lack of experience recognizing and treating cholera still plays a role in fatality rate in the early portion of the event life cycle. Later, as adaptation occurs, the CFR drops. Sites that do not demonstrate a drop in CFR are worthy of closer scrutiny to determine if, for example, medical resources are being depleted faster than they are being replenished. The graph for Cap Haitien city reveals a situation still very much in play and one we are monitoring closely with HEAS partners in the north.
In operational biosurveillance, we look back at such data periodically to validate prior operational awareness of events through social network-based alerting. The reason is related to the amount of time it takes to collect epidemiological data, analyze it, present and disseminate the information. For official bureaucracies, there is the additional step of public release approval. Thus, we operate through direct communication with community stakeholders affected and focus not necessarily on case counts but on the community's capacity to handle the challenge. Indicators such as anxiety level exhibited both in reporting and in the source (especially medical responders) are important to monitor, as is their ability to maintain dialog with the network. Responders dropping off the grid is an indication of concern, as it often indicates high strain. The quality of epidemiological data often suffers in crisis situations because of the triage of priorities: patient care comes first, not collecting data. Therefore, we consider epidemiological data within the broader sociological context. This is why operational alert and medical response functions, for the large part, operate independently of and in complement to public health functions when deaing with an infectious disease crisis or disaster (IDIS Cat 3-6 events).
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