Epidemic Risk after Disasters

To the Editor: We conduct communicable disease risk assessments after humanitarian emergencies, including natural disasters, and would like to clarify the findings of Floret et al. (1) regarding the risk for epidemics in certain disaster settings. Natural disasters that do not result in population displacement, regardless of type of disaster, are rarely associated with increased risk for epidemics. However, large-scale population displacement, with consequent overcrowding in temporary settlements and disruption of water supply and sanitation, are indeed associated with increased risks for communicable disease transmission. This distinction is well documented (2–4). Increased communicable disease incidence after flooding and cyclones has been particularly well described (5,6). In addition, after a disaster of any type, epidemics may go undetected because of poor surveillance or because baseline surveillance data for diseases (such as dengue fever or malaria) are unavailable. 
 
Although we agree with the authors that media reports are often exaggerated and that the risk for epidemics after certain types of natural disasters (e.g., volcanic eruption) is low, we believe the findings are somewhat misleading. Postdisaster communicable disease incidence is related more closely to the characteristics of the displaced population (size, health status, living conditions) than to the precipitating event.


Epidemic Risk after Disasters
To the Editor: We conduct communicable disease risk assessments after humanitarian emergencies, including natural disasters, and would like to clarify the findings of Floret et al. (1) regarding the risk for epidemics in certain disaster settings. Natural disasters that do not result in population displacement, regardless of type of disaster, are rarely associated with increased risk for epidemics. However, large-scale population displacement, with consequent overcrowding in temporary settlements and disruption of water supply and sanitation, are indeed associated with increased risks for communicable disease transmission. This distinction is well documented (2)(3)(4). Increased communicable disease incidence after flooding and cyclones has been particularly well described (5,6). In addition, after a disaster of any type, epidemics may go undetected because of poor surveillance or because baseline surveillance data for diseases (such as dengue fever or malaria) are unavailable.
Although we agree with the authors that media reports are often exaggerated and that the risk for epidemics after certain types of natural disasters (e.g., volcanic eruption) is low, we believe the findings are somewhat misleading. Postdisaster communicable disease incidence is related more closely to the characteristics of the displaced population (size, health status, living conditions) than to the precipitating event. In response: Watson et al. stressed some points that may be important determinants in assessing the risk for epidemics following natural disasters (1). We agree that large-scale population displacement, with overcrowding and water disruption, is clearly a risk factor for disease transmission. This factor was probably the main cause of the measles and diarrhea outbreaks that occurred in the temporary settlements created after the eruption of Mount Pinatubo in the Philippines, as mentioned in our previous article (2). However, by studying >600 geophysical disasters (earthquakes, volcano eruptions, and tsunamis) that occurred in the last 20 years, we found that deleterious conditions such as largescale population displacement with overcrowding and water disruption were uncommon and that epidemics were the exception, not the rule. We agree that some epidemics, especially if they are limited and develop well after the disaster, may remain undetected, as was discussed in our paper (1).
However, we do not concur with the opinion expressed by Watson et al. that the incidence of postdisaster infectious diseases is more related to the characteristics of the displaced population than to the precipitating event. Our findings are just the opposite. In contrast to the situation seen with flooding and cyclones, which are sometimes followed by outbreaks of waterborne diseases, such as cholera or leptospirosis, and vectorborne diseases (3-6), the study we carried out on geophysical disasters did not detect any notable outbreak except for the above-mentioned measles outbreak. Watson et al. illustrated their statement by referring to outbreaks following floods and hurricanes, and not earthquakes, tsunamis, or volcano eruptions. Further work must be carried out on epidemics after floods provoked by heavy rains and hurricanes. We assessed the utility of administrative databases, a computerized clinical data repository, and an electronic rule to enhance surveillance for CA-MRSA at Stroger (Cook County) Hospital, a 464-bed public safety net hospital in Chicago, and its associated clinics-all part of the Cook County Bureau of Health Services (CCBHS).
Using data collected within the Chicago Antimicrobial Resistance Project computerized clinical data repository (9) from September 1, 2001, to August 31, 2004, we developed an electronic rule to define persons with CA infection with S. aureus. This rule used the electronic records of all persons from whom MRSA or methicillin-susceptible S. aureus (MSSA) had been identified in cultures of soft tissue, pus, bone, or joints. Infections from patients who met the following electronic case definition were designated CA: 1) culture obtained as an outpatient or within the first 3 days of hospitalization, 2) no clinical culture with MRSA in the last 6 months, 3) no hospitalization or surgeries within 1 year, and 4) no hemodialysis. All other infections were defined as healthcare associated. Data for microbiology results, demographics, and recent surgery or hospitalization were linked by a unique patient identification number. Dialysis use was detected by the use of biochemical tests obtained around the time of dialysis or of hemodialyisrelated ICD-9 procedure codes (39.27, 90945, 39.95, 90935, 54.98, 39.43, 39.42, or 38.95). Because the electronic data sources were complete for the period specified, absence of data for a patient was considered to be due to the absence of exposure, not missing data.
Using the electronic case definition and data repository, we randomly selected 100 patients with putative CA-and 100 with putative healthcareassociated S. aureus infections. The paper charts for these 200 patients were reviewed to validate the designa-