IHR self-reported capacity
IHRMT is a questionnaire to monitor progress in implementing the IHR of countries (5). The questionnaire consists of 13 sections including 8 core capacities, points of entry and 4 ‘other hazards’ as identified and delineated by the WHO to match the obligations outlined in Annex 1 of the IHR. Eight core capacities mainly for infectious disease control include legislation, coordination, surveillance, response, preparedness, risk communication, human resources and laboratory. The 4 hazards include zoonosis, food safety, chemical and radionuclear. Individual questions were grouped by components and indicators in the questionnaires including 256 total attributes.
The response for IHRMT from countries comprises the percentage of implementation ranging from 0 to 100. We obtained countries’ self-reported implementation percentages as scores from the WHO website on 31rd October 2018 (17). One hundred countries’ self-reported IHRMT scores in 2016 were available and used in the study. While there are more countries (n = 160) reported IHR scores in 2017, we also collected self-reported IHRMT in 2017 for analysis. The average score of 8 core capacities was further calculated to represent overall national capacity regarding infectious disease control.
Infectious disease control outcomes
Based on the rationale that early detection and effective response to avoid further level up the pandemic is fundamental in infectious disease control, we use the report information from ProMED-mail and WHO Disease Outbreak News to be the indicator of infectious disease control outcome because both systems aim at early reporting of the outbreak and updated the development of the possible pandemic.
To evaluate infectious disease control outcomes, we first collected all disease outbreak reports in 2016 released on the WHO Disease Outbreak News website (18). Also, we collected all WHO outbreak reports concerning diseases, i.e., avian flu, yellow fever, and Middle East respiratory syndrome and coronavirus (MERS-CoV), those having been reported on the WHO website- from ProMED-mail in 2016. ProMED-mail is a nongovernmental emerging disease monitoring program established in 1994 to provide early warning about outbreaks based on information from various sources (19). The credibility of ProMED-mail and its efforts on reporting timely information were repeatedly confirmed by several studies (20-22). By collecting all sources of information including media reports, official reports, online summaries, local observers, and others without political constraints, reports on ProMED-mail is comprehensive. As an internet-based reporting system with electronic communications approach, the effect of reporting in a timely manner of ProMED-mail was also confirmed by previous study through comparing the timeliness of reporting form the WHO. Apart from the WHO, which reports “a public health emergency of international concern” regulated by IHR 2005, ProMED-mail aims at reporting all kinds of information on outbreaks of infectious diseases. Thus, we collected outbreak information from both websites to track countries’ infectious disease control situations. Reports containing only animal disease outbreaks were also collected.
As for multiple countries outbreak reports from WHO and ProMED-mail, each country report was separated as an individual case. Aside from initial outbreak reports, WHO Disease Outbreak News also posts reports labeled as “update”. These reports were examined for details indicating the spread of the initial outbreak to other regions in the affected countries. We searched ProMED-mail reports to match the information about the spread of outbreaks to other countries. Updates that mentioned only an increased number of cases without additional information about geographical spread within the country were excluded. Reports about WHO technical meetings and epidemiological survey findings were also excluded. Then we matched the outbreak reports of WHO and ProMED-mail based on the information revealed in the report including disease name, country and the date of onset and other details.
After matching, we ranked the infectious disease control outcomes of reports based on the rationale that the spread of infectious diseases was controlled right after their detection, and might represent better control outcomes of the country. Disease control outcomes were ranked in 4 levels. Reports containing only animal cases were ranked as level 1. Human disease reports which were only listed on ProMED-mail were ranked as level 2. Human disease outbreaks updated in ProMED-mail showing the spread of disease to other regions of the country were ranked as level 3. Lastly, the disease outbreaks listed on both ProMED-mail and the WHO website or only listed on the WHO website were ranked as level 4 (the worst), meaning that disease was out of control and had become a global concern.
We collected the earliest 10 cases from each rank to be the subset for a validation of ranking methodology. Two researchers individually ranked the cases into 4 levels based on the review of the outbreak information including case count (died, confirmed and suspected cases), spread, or other related indicators provided in the report. The agreement rate among these two researchers was 90%. And the average ranking level was parallel with the original ranking level.
Using this method, 907 reports were collected to analyze.
With the rationale that national infectious disease control capacity includes systematic elements like legislation and coordination and human resources as trained medical professionals (11, 23), we further searched the Human Development Index (HDI) from the United Nations Development Program (UNDP) and information from WHO regarding the density of physician and nurses and total health expenditure to represent the general health capacity of the country(2, 24).
Human development is defined as encompassing three dimensions: life expectancy at birth as an index of population health and longevity; knowledge and education as measured by the adult literacy rate and the combined primary, secondary and tertiary gross enrollment ratio and standard of living as measured by the natural logarithm of gross domestic product per capita at purchasing power parity. With indicators mainly collected from official statistics, the indexes of the three dimensions were expressed as a value between 0 and 1 by applying the general formula. Then the human development index was calculated as a simple average of the dimension indices ranging between 0 and 1, with 1 representing the highest degree of human development and 0 the lowest. We used the human development index of 2016 to represent the human development status of each country in that year. The details of methods to determine the values are described in the Technical Notes section of the report (24). In addition, the categories used by the UN, i.e., very high, high, medium and low development countries were also used in the study.
Information of each country’s density of physicians and nurses was collected from WHO websites (2). Then the sum of these two scores was calculated and used as the index of the health workforce in the study. We then categorized countries as having a high, middle or low health workforce according to the sum of the density of physicians and nurses in each country. Countries with upper tertile scores of health workforce density were defined as having a high health workforce. Countries with the middle and lower tertile scores of health workforce density were defined as having a middle and low health workforce, respectively.
Information of each country’s total health expenditure was also collected from WHO websites to represent the national investment in health. We then categorized countries into three groups: countries with upper tertile scores was defined as having a high total health expenditure, the others were defined as having a middle and low total health expenditure, respectively.
While the frequency of international travel increases the risk of infectious disease outbreak, we also collected information regarding the number of arrivals of international tourists from the World Bank to represent the risk of exposure to infectious diseases (4). The World Bank classifies the number of arrivals of international tourists in 10 levels. We reclassified countries in 2 international travel groups (high vs. low) using the cut-off point at level 5.
IHR average score was categorized as high, middle or low. Countries with upper tertile scores (≧97.6) were defined as having a high IHR average score. Countries with middle (88.89 to 97.5) and lower tertile scores (≦88.88) were defined as having middle and low IHR average scores, respectively. While the upper tertile point of IHR average score of 2017 was 99.25, we divided the scores into two levels, high vs. low, using the group mean (86.105) as the cut-off point to avoid the bias of excessive concentration.
Reports were further divided by disease control outcomes in 3 groups. Reports with a disease control level 1 and level 2 were classified as “good”. Reports with a disease control level 3 and 4 were classified as “normal” or “International alert or bad”.
Chi-square test was applied to compare differences among HDI, health workforce, international travel, total health expenditure and IHR self-reported scores among diverse disease control outcome groups. Then reports with normal or bad disease control outcomes were combined and analyzed further. Logistic regression was then adopted to estimate the associations among disease control outcomes and IHR self-reporting scores, HDI, health workforce and international travel. Two models were applied in the analysis where the regression was used for all cases and for only human cases separately.
All analysis was performed using the software SPSS, Version 18.0.