Implementation of an alert and response system in Haiti during the early stage of the response to the cholera epidemic

The start of the cholera epidemic in Haiti quickly highlighted the necessity of the implementation of an Alert and Response (A&R) System to complement the existing national surveillance system. The national system had been able to detect and confirm the outbreak etiology but required external support to monitor the spread of cholera and coordinate response, because much of the information produced was insufficiently timely for real-time monitoring and directing of a rapid, targeted response. The A&R System was designed by the Pan American Health Organization/World Health Organization in collaboration with the Haiti Ministry of Health, and it was based on a network of partners, including any institution, structure, or individual that could identify, verify, and respond to alerts. The defined objectives were to (1) save lives through early detection and treatment of cases and (2) control the spread through early intervention at the community level. The operational structure could be broken down into three principle categories: (1) alert (early warning), (2) verification and assessment of the information, and (3) efficient and timely response in coordination with partners to avoid duplication. Information generated by the A&R System was analyzed and interpreted, and the qualitative information was critical in qualifying the epidemic and defining vulnerable areas, particularly because the national surveillance system reported incomplete data for more than one department. The A&R System detected a number of alerts unrelated to cholera and facilitated rapid access to that information. The sensitivity of the system and its ability to react quickly was shown in May of 2011, when an abnormal increase in alerts coming from several communes in the Sud-Est Department in epidemiological weeks (EWs) 17 and 18 were noted and disseminated network-wide and response activities were implemented. The national cholera surveillance system did not register the increase until EWs 21 and 22, and the information did not become available until EWs 23 and 24, when the peak of cases had already been reached. Although many of the partners reporting alerts during the peak of the cholera epidemic have since left Haiti, the A&R System has continued to function as an Early Warning (EWARN) System, and it continues to be developed with recent activities, such as the distribution of cell phones to enhance alert communication.

Risk factors for severe outcomes following 2009 influenza A (H1N1) infection: a global pooled analysis

BACKGROUND

Since the start of the 2009 influenza A pandemic (H1N1pdm), the World Health Organization and its member states have gathered information to characterize the clinical severity of H1N1pdm infection and to assist policy makers to determine risk groups for targeted control measures.

METHODS AND FINDINGS

Data were collected on approximately 70,000 laboratory-confirmed hospitalized H1N1pdm patients, 9,700 patients admitted to intensive care units (ICUs), and 2,500 deaths reported between 1 April 2009 and 1 January 2010 from 19 countries or administrative regions--Argentina, Australia, Canada, Chile, China, France, Germany, Hong Kong SAR, Japan, Madagascar, Mexico, The Netherlands, New Zealand, Singapore, South Africa, Spain, Thailand, the United States, and the United Kingdom--to characterize and compare the distribution of risk factors among H1N1pdm patients at three levels of severity: hospitalizations, ICU admissions, and deaths. The median age of patients increased with severity of disease. The highest per capita risk of hospitalization was among patients <5 y and 5-14 y (relative risk [RR] = 3.3 and 3.2, respectively, compared to the general population), whereas the highest risk of death per capita was in the age groups 50-64 y and ≥65 y (RR = 1.5 and 1.6, respectively, compared to the general population). Similarly, the ratio of H1N1pdm deaths to hospitalizations increased with age and was the highest in the ≥65-y-old age group, indicating that while infection rates have been observed to be very low in the oldest age group, risk of death in those over the age of 64 y who became infected was higher than in younger groups. The proportion of H1N1pdm patients with one or more reported chronic conditions increased with severity (median = 31.1%, 52.3%, and 61.8% of hospitalized, ICU-admitted, and fatal H1N1pdm cases, respectively). With the exception of the risk factors asthma, pregnancy, and obesity, the proportion of patients with each risk factor increased with severity level. For all levels of severity, pregnant women in their third trimester consistently accounted for the majority of the total of pregnant women. Our findings suggest that morbid obesity might be a risk factor for ICU admission and fatal outcome (RR = 36.3).

CONCLUSIONS

Our results demonstrate that risk factors for severe H1N1pdm infection are similar to those for seasonal influenza, with some notable differences, such as younger age groups and obesity, and reinforce the need to identify and protect groups at highest risk of severe outcomes. Please see later in the article for the Editors' Summary.

Different transmission patterns in the early stages of the influenza A(H1N1)v pandemic: a comparative analysis of 12 European countries

Following the emergence of a novel strain of influenza A(H1N1) in Mexico and the United States in April 2009, its epidemiology in Europe during the summer was limited to sporadic and localised outbreaks. Only the United Kingdom experienced widespread transmission declining with school holidays in late July. Using statistical modelling where applicable we explored the following causes that could explain this surprising difference in transmission dynamics: extinction by chance, differences in the susceptibility profile, age distribution of the imported cases, differences in contact patterns, mitigation strategies, school holidays and weather patterns. No single factor was able to explain the differences sufficiently. Hence an additive mixed model was used to model the country-specific weekly estimates of the effective reproductive number using the extinction probability, school holidays and weather patterns as explanatory variables. The average extinction probability, its trend and the trend in absolute humidity were found to be significantly negatively correlated with the effective reproduction number - although they could only explain about 3% of the variability in the model. By comparing the initial epidemiology of influenza A (H1N1) across different European countries, our analysis was able to uncover a possible role for the timing of importations (extinction probability), mixing patterns and the absolute humidity as underlying factors. However, much uncertainty remains. With better information on the role of these epidemiological factors, the control of influenza could be improved.