The cost of influenza-associated hospitalizations and outpatient visits in Kenya.

BACKGROUND: We estimated the cost-per-episode and the annual economic burden associated with influenza in Kenya. METHODS: From July 2013-August 2014, we recruited patients with severe acute respiratory illness (SARI) or influenza-like illness (ILI) associated with laboratory-confirmed influenza from 5 health facilities. A structured questionnaire was used to collect direct costs (medications, laboratory investigations, hospital bed fees, hospital management costs, transportation) and indirect costs (productivity losses) associated with an episode of influenza. We used published incidence of laboratory-confirmed influenza associated with SARI and ILI, and the national population census data from 2014, to estimate the annual national number of influenza-associated hospitalizations and outpatient visits and calculated the annual economic burden by multiplying cases by the mean cost. RESULTS: We enrolled 275 patients (105 inpatients and 170 outpatients). The mean cost-per-episode of influenza was US$117.86 (standard deviation [SD], 88.04) among inpatients; US$114.25 (SD, 90.03) for children < 5 years, and US$137.45 (SD, 76.24) for persons aged ≥5 years. Among outpatients, the mean cost-per-episode of influenza was US$19.82 (SD, 27.29); US$21.49 (SD, 31.42) for children < 5 years, and US$16.79 (SD, 17.30) for persons aged ≥5 years. National annual influenza-associated cost estimates ranged from US$2.96-5.37 million for inpatients and US$5.96-26.35 million for outpatients. CONCLUSIONS: Our findings highlight influenza as causing substantial economic burden in Kenya. Further studies may be warranted to assess the potential benefit of targeted influenza vaccination strategies.

Estimating influenza and respiratory syncytial virus-associated mortality in Western Kenya using health and demographic surveillance system data, 2007-2013.

BACKGROUND: Influenza and respiratory syncytial virus (RSV) associated mortality has not been well-established in tropical Africa. METHODS: We used the negative binomial regression method and the rate-difference method (i.e. deaths during low and high influenza/RSV activity months), to estimate excess mortality attributable to influenza and RSV using verbal autopsy data collected through a health and demographic surveillance system in Western Kenya, 2007-2013. Excess mortality rates were calculated for a) all-cause mortality, b) respiratory deaths (including pneumonia), c) HIV-related deaths, and d) pulmonary tuberculosis (TB) related deaths. RESULTS: Using the negative binomial regression method, the mean annual all-cause excess mortality rate associated with influenza and RSV was 14.1 (95% confidence interval [CI] 0.0-93.3) and 17.1 (95% CI 0.0-111.5) per 100,000 person-years (PY) respectively; and 10.5 (95% CI 0.0-28.5) and 7.3 (95% CI 0.0-27.3) per 100,000 PY for respiratory deaths, respectively. Highest mortality rates associated with influenza were among ≥50 years, particularly among persons with TB (41.6[95% CI 0.0-122.7]); and with RSV were among <5 years. Using the rate-difference method, the excess mortality rate for influenza and RSV was 44.8 (95% CI 36.8-54.4) and 19.7 (95% CI 14.7-26.5) per 100,000 PY, respectively, for all-cause deaths; and 9.6 (95% CI 6.3-14.7) and 6.6 (95% CI 3.9-11.0) per 100,000 PY, respectively, for respiratory deaths. CONCLUSIONS: Our study shows a substantial excess mortality associated with influenza and RSV in Western Kenya, especially among children <5 years and older persons with TB, supporting recommendations for influenza vaccination and efforts to develop RSV vaccines.

Influenza activity in Kenya, 2007-2013: timing, association with climatic factors, and implications for vaccination campaigns.

BACKGROUND: Information on the timing of influenza circulation remains scarce in Tropical regions of Africa. OBJECTIVES: We assessed the relationship between influenza activity and several meteorological factors (temperature, specific humidity, precipitation) and characterized the timing of influenza circulation and its implications to vaccination strategies in Kenya. METHODS: We analyzed virologically confirmed influenza data for outpatient influenza-like illness (ILI), hospitalized for severe acute respiratory infections (SARI), and cases of severe pneumonia over the period 2007-2013. Using logistic and negative binomial regression methods, we assessed the independent association between climatic variables (lagged up to 4 weeks) and influenza activity. RESULTS: There were multiple influenza epidemics occurring each year and lasting a median duration of 2-4 months. On average, there were two epidemics occurring each year in most of the regions in Kenya, with the first epidemic occurring between the months of February and March and the second one between July and November. Specific humidity was independently and negatively associated with influenza activity. Combinations of low temperature (<18°C) and low specific humidity (<11 g/kg) were significantly associated with increased influenza activity. CONCLUSIONS: Our study broadens understanding of the relationships between seasonal influenza activity and meteorological factors in the Kenyan context. While rainfall is frequently thought to be associated with influenza circulation in the tropics, the present findings suggest low humidity is more important in Kenya. If annual vaccination were a component of a vaccination strategy in Kenya, the months of April to June are proposed as optimal for associated campaigns.

Influenza vaccination policy-making processes in France and The Netherlands: Framework and determinants.

OBJECTIVES: Target groups for seasonal influenza vaccination are nationally defined based on several factors. However, few studies have explored the policy-making processes at the country-level. We investigated key differences in the policy-making process for the development of vaccination recommendations between France (FR) and The Netherlands (NL). This paper presents preliminary results on the evidence used in the decision-making process and focuses on the interactions between the experts and stakeholders. METHODS: A documentary analysis identified the stakeholders of this process as governmental authorities, research institutions, associations, and manufacturers. This qualitative study included at least one expert from each stakeholder group. Thirty-three semi-structured interviews were performed in 2013 (16 FR, 17 NL). We used NVivo10® to perform a thematic content analysis on the data. RESULTS: National Immunization Technical Advisory Groups (NITAGs) were the key stakeholders in the development of recommendations. There was no systematic standard evaluation of evidence during the decision-making process in both countries. Likewise, voting was not systematic, although it did occur more often in FR. A declaration of interests was obligatory in both countries. Experts with no conflicts of interest were rare because many depend on private funding for their research on influenza vaccination. CONCLUSIONS: The transparency of the NITAGs' procedures for the development of recommendations should be improved. We believe improvements might be achieved by the systematic standard evaluation of evidence, consistent voting, clear declarations of interest, and increased public funding for vaccination research.

Variation of respiratory syncytial virus and the relation with meteorological factors in different winter seasons.

BACKGROUND: Respiratory syncytial virus (RSV) is the most important viral agent causing severe respiratory disease in infants and children. In temperate climates, RSV activity typically peaks during winter. We have described the seasonal variation in RSV activity and investigated which meteorological variables are related to RSV outbreaks for different time lags. METHODS: Eleven laboratories in the Netherlands collected data on RSV during the period 1998-2005. Meteorological data were obtained from the Royal Netherlands Meteorological Institute. General linear methods were used to determine the relative contribution of meteorological conditions to reported RSV cases in the winter period. Time lags up to 4 weeks were included to assess a possible delayed weather effect in relation to RSV activity. RESULTS: Onset of RSV activity occurred around week 44 and activity peaked around week 52. Timing of peak activity was very consistent over the study period. Relative humidity was positively associated with RSV activity for all time lags, indicating more RSV when relative humidity increased. Minimum temperature was negatively associated with RSV activity and cloud cover was positively related with RSV activity. Interaction (P < 0.06) between minimum temperature and relative humidity was observed for a lag of 0, 1, and 2 weeks, indicating that the combination of low temperature and high humidity contributes more to RSV activity than temperature and humidity alone. CONCLUSIONS: Relative humidity, minimum temperature, and cloud cover are important predictors of RSV activity in the Netherlands, with the effect of relative humidity being most consistent.