Blog
About

31
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Science Avant-Garde

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Paul Signac (1863–1935) La salle à manger, Breakfast (1886–1887) Oil on canvas (89.5 cm × 116.5 cm) Kröller-Müller Museum, Otterlo, the Netherlands www.kmm.nl/ “To think that the neoimpressionists are painters who cover canvases with little multicolored spots is a rather widespread mistake,” wrote Paul Signac in his manifesto of their movement. “This mediocre dot method has nothing to do with the aesthetic of the painters we are defending here, nor with the technique of divisionism they use.” Signac was referring to, among others, Georges Seurat, who in trying to systematize the optical discoveries of the impressionists, had taken a scientific approach to painting, one based on color theory. His goal, he once said, was to make “modern people, in their essential traits, move about as if on friezes, and place them on canvases organized by harmonies of color, by directions of the tones in harmony with the lines, and by the directions of the lines.” Signac wholeheartedly adopted Seurat’s invention, pointillism or divisionism, though he considered it simply a means of expression, a way to apply paint to the canvas. “The dot is nothing more than a brushstroke, a technique. And like all techniques, it does not matter much.” The idea was to render the surface of a painting more vibrant, to maximize the brilliance of color. But the methodical scientific technique alone did not “guarantee luminosity or the intensity of colors or harmony. This is due to the fact that complementary colors are favorable to and intensify each other when they are blended, even optically. A red surface and a green surface, when adjacent, stimulate one another. Red dots blended into green dots produce a gray and colorless whole.” “My family wanted me to become an architect, but I preferred drawing on the banks of the Seine rather than in a workshop of the École des Beaux-Arts,” wrote Signac. A visit to an exhibition of Claude Monet in 1880 was a life-changing experience. After a brief stint at the Collège Rollin, he set out to become a painter, which he did, a stellar one and self-taught. His earliest work was filled with energy. “It consisted in pasting reds, greens, blues, and yellows, without much care but with enthusiasm.” When he lost his father to tuberculosis, his financially stable and supportive family saw to it he did not have to make ends meet. The same year, at age 17, he bought a painting by Paul Cézanne. His own first painting was dated a year later. Signac spent most of his life in and around Paris where he was born. He was interested in science, literature, and politics. He was a writer, whose poetic sensitivity found its way into landscape painting. He was an avid traveler. His Olympia, a boat named after Édouard Manet’s famed nude, took him to Italy, Holland, and Constantinople. He often stopped to paint Mediterranean ports and scenery, immortalizing the French coast in watercolors painted en plein air. Although he experimented with oils, pen and ink, etchings, and lithographs, watercolor, “a playful game,” was the mainstay of his life’s work. “I have seen Signac, and it has done me quite a lot of good,” wrote Vincent van Gogh to his brother Theo. “He was so good and straightforward and simple …. I found Signac very quiet though he is said to be violent; he gave me the impression of someone who has balance and poise.” Signac’s irrepressible vitality and exuberance, his love of action and the outdoors, and a native combativeness were at times misunderstood, but not by his many friends, an array of artists and anarchists. Unassuming and ragged in his sailor’s garb, he was often at sea or at his home in St. Tropez, a meeting place for the exchange and promotion of artistic ideas. Signac equated social revolution with artistic freedom. “The anarchist painter is not the one who will create anarchist pictures, but he who, without desire for recompense, will fight with all his individuality against official bourgeois conventions by means of a personal contribution.” At age 21, Signac became, along with Georges Seurat and others, cofounder of the Société des Artistes Indépendants, a group intended to provide opportunities for exhibiting avant-garde works away from the rigid cultural politics of the Paris Salon. President of the society from 1908 until his death, Signac encouraged young artists by exhibiting controversial works. Meanwhile, with Seurat, he set off to articulate the theories of neoimpressionism. After the untimely death of Seurat from respiratory infection at age 31, Signac became the sole advocate and leader of the movement. Signac took Seurat’s theories to a new level. Armed with watercolor sketches from nature, he moved the studio indoors and used mosaic-like squares of pure color to compose large scenes that would influence the works of van Gogh and Gauguin, inspire Matisse, and affect the evolution of future art movements, from fauvism to cubism. Signac was tireless in explaining divisionism. “In order to listen to a symphony, you don’t sit in the middle of the orchestra but in the position where the sounds from the various instruments mingle, creating the harmony desired by the composer. Similarly, faced by a ‘divided’ painting, it is best to first stand at a sufficient distance in order to absorb the whole, before moving closer to study the chromatic effects up close.” For the first 20 years of his career, he received little recognition and neoimpressionism received negative criticism, even by those who initially supported it. He died of septicemia in Paris at 72. La salle à manger, Breakfast, on this month’s cover, is from a series of views inside contemporary interiors with figures usually posed in stiff profile. Signac valiantly sought art solutions in the scientific process, the precise observation of color tones in close proximity. And, moving away from the subjectivity of impressionism and the passing moment, he searched the small particles of color for truth. Always interested in human psychology and social justice, he looked for them in home interiors, as he curiously observed the urban middle-class. In Breakfast, he spied on them from outside the room, inviting the viewer to do the same. With scant interest in perspective, he placed the human figures on a grid, same as all other objects. Frozen in space and time, these figures were not persons but social types: the retired bourgeois, the maid, the housewife. Uninterested in each other, they played roles, their performance an indictment of society and marriage, which inhibits the development of individual personality. “By exclusive use of … pure colors, by methodical division and by observing the scientific theory of colors, [the neoimpressionist] guarantees maximal luminosity, color, and harmony to an unprecedented degree,” Signac wrote. The painter’s vision applies neatly to today’s rapid advancement of genome technologies that, by providing tiny bits of data on disease-causing microbes, promise to improve the canvas of clinical and public health laboratory investigations and lower the costs. The latest genome DNA sequencers generate detailed and robust information for clinical and public health laboratories and could spawn a global system of linked databases of pathogen genomes to ensure more efficient detection, prevention, and control of endemic and emerging diseases and all manner of outbreaks. Even as these new genomic tools enhance diagnosis, they decrease the use of culture and molecular methods that produce data currently critical for epidemiologic investigation. Careful application of current epidemiologic techniques teases apart the dynamic interaction of infectious diseases that drive total illness and death rates up or down, even in outbreaks with universal exposure. New genome-backed epidemiologic approaches will be needed as sequencers replace culture and molecular techniques so this ability is not lost. “To ensure optical mixture, the neoimpressionists were forced to use brushwork of a small scale so that, when standing back sufficiently, different elements could reconstitute the desired tint and not be perceived in isolation.” In genomics approaches, likewise, field epidemiologists must use alternative data sources or original techniques to capture the unique characteristics that tie together the epidemiologically related whole. Without these, the bits provided by the precise genomic tools would only create “industrial art,” a canvas without valuable content, aesthetics achieved, in Signac’s words, by “empirical formulae and dishonest or silly advice.”

          Related collections

          Most cited references 4

          • Record: found
          • Abstract: found
          • Article: not found

          Coccidioidomycosis-associated Deaths, United States, 1990–2008

          Coccidioidomycosis is a fungal disease that occurs throughout the Americas. It is contracted by inhaling spores, which are carried in dust. Therefore, it occurs most commonly in dry areas and in persons who work in dusty conditions (such as agricultural workers, construction workers, military personnel, and archeological site workers). A substantial number of people die of this disease each year, so researchers examined what other factors increase the risk for death. They found that risk for death was highest among men, elderly persons (>65 years), Hispanics, Native Americans, residents of California and Arizona, and those who also had HIV or other immune-suppressive conditions. Physicians should be aware of which patients are at increased risk and should ask patients about their travel history or occupation to determine possible sources of exposure.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            HIV Infection and Geographically Bound Transmission of Drug-Resistant Tuberculosis, Argentina

            During the early 1990s, HIV-associated multidrug-resistant tuberculosis (MDR TB) emerged in Argentina ( 1 ). In Buenos Aires, the country’s most heavily populated city, certain multidrug-resistant Mycobacterium tuberculosis strains spread quickly among patients with AIDS ( 2 , 3 ). Specifically, the so-called M strain caused a major MDR TB outbreak at the Hospital Muñiz, a referral treatment center for infectious diseases ( 4 ). HIV-infected patients repeatedly seeking assistance at different health centers introduced the M strain into hospitals in nearby districts, where secondary transmission occurred ( 5 ). This strain was later responsible for the emergence of MDR TB in HIV-negative patients who had not previously undergone TB treatment ( 6 ). In 2002, the M strain was isolated from 2 patients with extensively drug-resistant TB (XDR TB). Two other MDR TB outbreak strains, Ra and Rb, emerged in Rosario, the third largest city in Argentina, simultaneously with the M strain ( 7 ). MDR TB emergence highlighted the need for a MDR/XDR TB surveillance system focused on incidence and transmission. In 2003, the National TB Laboratory Network launched a systematic registry of all incident MDR/XDR TB cases diagnosed throughout the country. The registry includes a genotype database for all MDR/XDR TB patients going back to the initial outbreaks and population studies. We present the findings of a 7-year follow-up study of MDR and XDR TB in Argentina, with emphasis on potential transmission events involving strains responsible for previous outbreaks. Materials and Methods Study Group Isolates from all patients with newly diagnosed MDR or XDR TB from January 2003 through December 2009 were included in the study (1 isolate per patient, collected at time of diagnosis). MDR TB was defined as disease caused by M. tuberculosis resistant to at least isoniazid and rifampin and XDR TB as disease caused by MDR M. tuberculosis showing further resistance to any fluoroquinolone and any second-line injectable anti-TB drug. A patient with newly diagnosed MDR or XDR TB was defined as a patient with disease first confirmed by drug susceptibility testing (DST) during the study period, regardless of previous treatment history. A hotspot was defined as an area where a MDR TB outbreak had been documented before the study period. Two or more patients were considered to be epidemiologically related when they were in the same place and time or shared similar behavioral risk factors. Available demographic and clinical data were collected through the national TB laboratory network. A special effort was made to retrieve data from clinical records in special groups, i.e., XDR TB, patients in hotspot areas, and those in clusters with 6 bands, a cluster was defined as a group of >2 isolates whose RFLP patterns and spoligotypes were 100% identical when compared with all other patterns found within the study period. RFLP patterns with 15 patients and a minor cluster as 45 years of age. Gender was removed from the models because it was associated with particular settings in 2 major clusters; unknown categories were removed from all the variables included in the model. Because of the limited numbers per category, the age category 0.5, and area under the curve >0.70. We used the χ2 test for linear trends for assessing changes in the annual number of MDR TB patients in cluster M compared with changes in numbers in other major clusters. Statistical analyses were performed by using MedCalc version 12 software (MedCalc, Mariakerke, Belgium). Results MDR TB Patients, Genotypes, and Clustering Genotyping Coverage Genotyping was available for isolates from 787/830 (94.8%) newly diagnosed MDR TB patients registered during the study period (2003, 93.2%; 2004, 97.7%; 2005, 99.1%; 2006, 86.4%; 2007, 93.0%; 2008, 96.5%; 2009, 97.5%) (Figure 1). Coverage was lower in 2006 because of a technical mishap that resulted in a loss in the isolate collection. Figure 1 Numbers of patients with newly diagnosed multidrug-resistant tuberculosis reported per year, grouped according to genotype analysis, Argentina, 2003–2009. Major cluster, >15 patients; minor cluster, 45 121 63.6 1 1 48.3 1 1 Country of birth, n = 541 Argentina 412 80.1 2.7 (1.7–3.9) 3.5 (1.9–6.4) 66.7 7.6 (4.7–12.1) 8.0 (4.3–15.0) Other 129 61.2 1 1 20.9 1 1 Place of diagnosis, n = 787 Hotspot¶ 634 77.9 2.1 (1.5–3.1) 1.6 (0.7–3.7) 62.3 4.2 (2.9–6.2) 5.9 (2.5–13.8) Other 153 62.1 1 1 28.1 1 1 HIV status, n = 604 Positive 254 86.6 2.7 (1.7–4.1) 2.4 (1.0–5.6) 76.4 3.3 (2.-4.7) 3.7 (1.8–7.7) Negative 350 70.9 1 1 49.4 1 1 Previous TB, n = 557 Yes 313 71.9 0.7 (0.5–1.0) 0.8 (0.5–1.5) 51.8 0.7 (0.5–1.0) 0.7 (0.4–1.2) No 244 79.1 1 1 59.4 1 1 Site of disease, n = 775 Pulmonary only 698 74.1 0.6 (0.3–1.2) 1.4 (0.5–4.2) 55.0 0.8 (0.5–1.3) 2.7 (1.1–7.0) Other 77 81.8 1 1 59.7 1 1 *Boldface indicates significance. TB, tuberculosis; OR, odds ratio; ND, not done.
†Cluster model overall model fit p 15 patients in the study period.
§Major cluster model overall model fit p 3 drugs M 228 2 (0.9) 13 (5.7) 30 (13.2) 183 (80.3) Ra 89 8 (9.0) 61 (68.5) 15 (16.9) 5 (5.6) Rb 38 26 (68.4) 6 (15.8) 4 (10.5) 2 (5.3) Pr 26 26 (100) 0 0 0 At 21 6 (28.6) 5 (23.8) 6 (28.6) 4 (19.0) Ob 18 13 (72.2) 0 3 (16.7) 2 (11.1) Os 18 0 2 (11.1) 5 (27.8) 11 (61.1) *Additional drugs tested were streptomycin, ethambutol, pyrazinamide, kanamycin, amikacin, capreomycin, and ofloxacin. Figure 2 IS6110 restriction fragment length polymorphism (RFLP) patterns and spoligotypes of 7 major cluster strains, including 2 main variants of M strain, and reference strain Mt 14323. SIT, Shared International Type in SITVIT database (www.pasteur-guadeloupe.fr:8081/SITVIT). Figure 3 Locations of 7 major multidrug-resistant tuberculosis clusters, labeled by strain type, Argentina, 2003–2009. The predominant cluster, M, was largely confined to the city of Buenos Aires and the surrounding area, with only 5/228 patients having MDR TB diagnosed elsewhere. Twenty patients in this cluster were immigrants from neighboring countries (Bolivia 11, Paraguay 6, Peru 2, Uruguay 1). Most patients had >1 commonly acknowledged risk factors for MDR TB (129 patients had 1, 64 had 2, and 16 had 3 risk factors) (Table 3). The cluster included the 2 previously reported outbreak variants of the M strain ( 4 ), Mm in 180 patients and Mn in 35 patients (Figure 2), and 9 sporadic variants, observed in 13 patients who had proven epidemiologic links with other patients in cluster M. An isolate resistant to 5 drugs was strongly associated with disease produced by the M strain (Table 5). The numbers of patients affected by this strain decreased significantly within the period when compared with the numbers of patients in the other 6 major clusters (p = 0.002). In particular, the proportion of HIV-infected patients affected by the M strain decreased significantly during the study period, from 65% in 2003 to 24% in 2009 (p = 0.02; Figure 4). No similar trend was observed in the HIV-negative group (p = 0.77). Table 5 Predictors for being in cluster M among 438 patients with multidrug-resistant TB who were in clusters of >15 patients, Argentina, 2003–2009* Characteristic No. patients % Patients in M cluster Unadjusted OR (95% CI) Adjusted OR (95% CI)† Age, y, n = 347 16–45 288 50.7 0.9 (0.5–1.6) 1.4 (0.5–4.3) >45 59 52.5 1 1 Country of birth, n = 302 Argentina 275 51.0 0.7 (0.3–1.6) 0.6 (0.1–2.3) Other 27 74.1 1 1 HIV status, n = 360 Positive 194 60.3 1.6 (1.0–2.4) 1.4 (0.6–3.3) Negative 166 49.4 1 1 Previous TB treatment, n = 304 Yes 160 47.5 1.0 (0.7–1.6) 0.8 (0.4–1.8) No 144 46.5 1 1 Hospital exposure‡ Yes 86 72.1 2.9 (1.7–4.8) 2.6 (1.0–6.8) No 352 47.2 1 1 Isolate resistant to >5 drugs 207 88.4 31.5 (18.4–53.9) 22.7 (10.1–50.9) 45 8 87.5 50.0 Unknown (adult) 5 60.0 60.0 Country of birth Argentina 30 76.7 53.3 Other (South America)† 11 81.8 63.6 Unknown (South America)‡ 11 81.8 72.7 Indonesia 1 0 0 Place of diagnosis Former MDR TB hot spot 31 74.2 71.0 Other 22 81.8 40.9 HIV status Positive 14 85.7 78.6 Negative 33 75.8 54.5 Unknown 6 66.7 33.3 Site of disease Pulmonary 49 81.6 61.2 Disseminated 3 33.3 33.3 Unknown 1 0 0 Previous TB Yes 38 71.1 50.0 No 10 90.0 70.0 Unknown 5 100.0 100.0 AFB smear microscopy Positive 41 78.0 56.1 Negative 7 71.4 57.1 Unknown 5 75.0 75.0 *TB, tuberculosis; MDR, multidrug-resistant; AFB, acid-fast bacilli.
†From a country in South America other than Argentina
‡From an unknown country in South America. Table 7 Number of patients with extensively drug-resistant tuberculosis of different genotypes, by year, Argentina, 2003–2009 Genotype No. patients in year Total no. (%) patients 2003 2004 2005 2006 2007 2008 2009 Cluster M 5 4 5 2 0 3 2 21 (39.6) Cluster Rb 0 0 0 0 0 1 0 1 (1.9) Cluster At 0 1 0 0 0 0 1 2 (3.8) Cluster Os 0 0 2 1 2 1 1 7 (13.2) Minor cluster* 2 1 3 3 1 1 0 11 (20.8) Unique pattern 2 2 2 1 1 0 3 11 (20.8) Total 9 8 12 7 4 6 7 53 (100.0) *Cluster of 5 anti-TB drugs was found to be a strong predictor of disease caused by the M strain ( 4 , 26 ). The accumulation of drug resistance–conferring mutations would be expected to have reduced the epidemiologic fitness of this strain, but it has prevailed for 15 years. The epidemiologic fitness of a strain can be influenced by a range of factors, e.g., the genetic backgrounds of host and pathogen, host–pathogen interactions, and the environment ( 27 – 29 ). Compensatory evolution restoring in vivo fitness, as well as social and behavioral factors, might have played a role in the epidemiologic persistence of the M strain ( 30 ). These factors might also have preferentially fostered the spread of drug-resistant strains of the H2 genotype in our setting. Further studies are needed to evaluate the most critical risk factors. Drug-resistance profiles were not uniform within the M strain clusters. The variations in susceptibility to individual drugs reflect the existence of various ongoing chains of transmission, some of which might have started before, or simultaneously with, the first documented outbreak. One limitation of our study is the failure to identify individual chains. Factors that precluded the reliable characterization of subclusters were the long time elapsed since the outbreak onset, the insufficient epidemiologic documentation in many cases, and the unavailability of additional molecular markers. Our study has another major limitation. Incomplete demographic and clinical data on patients were retrieved, and several observations had missing values. If missing values were systematically associated with a given force or factor, results presented here would be biased. We are not aware of any association of missing values with the dependent variables under study and assume that those data were missing at random. Missing values may have affected the analyses by reducing the number of observations, which may have reduced the power of the model to detect significant associations but without necessarily biasing the associations reported. However, the possibility that bias might have resulted from missing data cannot be ruled out. Therefore, statistical significances of our analyses should be interpreted cautiously. In the MDR TB hotspots in Argentina, the distinction between primary and acquired MDR TB on the basis of a history of previous TB treatment was not decisive because patients could have been exposed to hospital-associated MDR TB infection while being treated for community-acquired TB. This fact could explain why clustering was not more frequent among patients without previous TB treatment in our study. The national TB network includes all the laboratories performing bacteriological TB diagnosis in the country; therefore, the patients in this study represent all newly diagnosed MDR TB cases in Argentina. The structure, geographic coverage, and personnel of the TB laboratory network are adequate to provide DST for all patients at risk for MDR TB in Argentina. However, a few MDR TB patients might remain undiagnosed because of operational factors, e.g., inefficient detection of risk factors, insufficient or delayed requests for DST, and disorganized information systems. The geographically restricted distribution of successful MDR TB genotypes that we found has public health implications. As a result of this study, specific interventions are being reinforced, particularly in the MDR TB hotspots: implementing universal culture and strategies to expedite drug resistance detection; decentralizing specialized health care; streamlining information-sharing systems between HIV and TB programs; and strengthening administrative infection control measures in prisons and large hospitals with high TB infection load. A national advisory group on MDR TB clinical management has also been recently created. Control interventions have already started to reduce MDR TB spread in the hospital that was the epicenter of the main outbreak ( 17 ). Still, centrally coordinated actions are needed in Argentina to curb long-term transmission of MDR TB.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Infectious Disease Mortality Rates, Thailand, 1958–2009

              Infectious diseases were responsible for a considerable number of deaths in Thailand during the mid–twentieth century ( 1 ). During 1948–1955, as Thailand experienced substantial economic and social development and transitioned from an agricultural to an urban and industrial society ( 2 ), the mortality rate began to decline ( 3 ). In 1968, infectious diseases such as tuberculosis (TB) and pneumonia were the main cause of death in Thailand; fewer deaths were caused by noninfectious diseases (e.g., diseases of the heart, malignancies). However, in the early 1980s, an epidemiologic transition was taking place, and non-communicable diseases became of greater public health concern ( 4 ). In contrast with the low mortality rates in many industrialized countries, where communicable diseases are well controlled ( 5 , 6 ), mortality rates in Thailand remained relatively high. However, the emergence of HIV/AIDS contributed to an increase in deaths in the 1990s and interrupted the epidemiologic transition ( 7 , 8 ). Communicable diseases are still responsible for a considerable number of illnesses (10% of total diseases in 2009) and deaths in Thailand ( 9 ). Because of the increasing threat from emerging and reemerging infectious diseases, it is vital to understand the patterns of infectious disease–related deaths in a country that has undergone economic development and concurrent improvements in health, sanitation, and access to healthcare. We used publicly available vital statistics for deaths in Thailand to analyze trends in infectious disease mortality rates during 1958–2009. This assessment helps us better understand past trends and inform policy on current infectious diseases of public health concern. Methods Source of Data Death-related data were obtained from a published series called the Report of Public Health Statistics (Bureau of Policy and Strategy, Ministry of Public Health [MOPH], Nonthaburi, Thailand). The reports summarize data, by year, from death certificates provided by the MOPH in collaboration with the Ministry of Interior (MOI) as part of the Vital Registration System. The MOI is responsible for registering deaths at the local administrative level; the MOPH is responsible for processing vital statistics data for the whole country and for disseminating the information on an annual basis through publication of the Report of Public Health Statistics. Death certificates record only 1 cause of death, which is the underlying cause of death. Using data from 1958–2009, we created an electronic database from the series of Report of Public Health Statistics. The database provided aggregated information on the total number and rate of deaths by age group, sex, year of death, and cause of death. Cause of death was coded according to the International Classification of Disease (ICD). During 1958–2009, the following ICD revisions were used: 1958–1967, ICD version 7 (ICD-7); 1968−1976, ICD-8; 1977–1993, ICD-8; and 1994–2009, ICD-10. For each ICD revision, death data were grouped differently, resulting in different group numbers for the ICD versions: ICD-7, 50 groups; ICD-8, 150; ICD-9, 56; and ICD-10, 103. During 1958–1983, mortality rates were calculated by using population denominator data from the Population and Housing Censuses conducted in 1960, 1970, and 1980. The estimated population between census years was adopted from the Report of the Working Group on Population Projection. After 1984, the annual mid-year estimated population was obtained from the Bureau of Registration Administration, MOI. Determination of Infectious versus Noninfectious Disease To assess trends in deaths caused by infectious diseases, we applied a classification scheme developed at the Centers for Disease Control and Prevention (CDC, Atlanta, GA, USA) ( 6 ). This coding system used ICD-9 codes to classify infection-associated diseases as 1) an infectious disease (e.g., pneumonia), 2) possibly an infectious disease (e.g., pityriasis rosea), and 3) result of an infectious disease (e.g., rheumatic fever). The system was developed to address the exclusion of some infectious diseases from the infectious disease category of the ICD system, e.g., influenza, which was placed in the respiratory disease category. For the purposes of this study only, those diseases classified as an infectious disease or as the result of an infectious disease ( 1 , 3 ) were used to classify deaths from infectious disease. Several adjustments were made to the original coding system. First, we had to account for deaths that were reported by using grouped ICD codes without distinction for infectious versus noninfectious disease (e.g., bronchitis, emphysema, and asthma are grouped in ICD-7). Deaths were reported by using only the shorter, less detailed 3-digit codes rather than the 4-digit subcodes used in the CDC classification system; thus, we re-coded as infectious any 3-digit codes for which >80% of the subcodes were for infectious diseases, and we re-coded as noninfectious any 3-digit codes for which 65 years); because of the structure (aggregate data) of the database, it was not possible to age-adjust other rates. Results Overall Mortality Rate Trends The all-cause mortality rate during 1958–2009 was characterized by a decrease during 1958–1986 and an increase during 1987–2009; however, in the early 2000s, the rate leveled (Figure 1). The average annual decrease for 1958–1986 was 2.8 deaths/100,000 population (95% CI 14.1%–11.5%) and average increase for 1987–2009 was 10.8 deaths/100,000 population (95% CI 9.3%–12.4%). The pattern was similar for both sexes, but the annual rate for males consistently exceeded that for females (Figure 1). Figure 1 All-cause mortality rates, Thailand, 1958–2009. The all-cause mortality rate varied by age group, but it was among persons >65 years of age (Figure 2). The highest average annual decline in the mortality rate was among children 65 years of age. Infectious Disease Mortality Rate Trends From 1958 through the late 1990s, the infectious disease mortality rate in Thailand declined 5-fold, from 163.4 deaths/100,000 population in 1958 to 29.5/100,000 in 1997 (average annual reduction 3.2 deaths/100,000 population; 95% CI 2.8%–3.7%) (Figure 3). This decline paralleled the decline in overall deaths from 1958 to the late 1990s. In 1998, infectious disease–related mortality rates started to increase and the trend continued through 2003 (average annual increase 7.6 deaths/100,000 population; 95% CI 5.9%–9.4%). In 2004, infectious disease–related deaths began to decline again; during 2004–2009, the average annual reduction was 3.5 deaths/100,000 population. Figure 3 Mortality rates for infectious and noninfectious diseases, Thailand, 1958–2009. A) Infectious disease–related mortality rates, major events, and key public health interventions. B) Comparison of infectious disease–related mortality rates with noninfectious disease–related mortality rates. EPI, Expanded Program on Immunization; BCG, Bacillus Calmette–Guérin vaccine; DTP, diphtheria, tetanus, and pertussis vaccine; OPV, oral polio vaccine; ARV, antiretroviral treatment; DOTS, directly observed treatment, short course. Mortality rates for several specific infectious diseases declined during 1958–2009 (Figure 4). For example, malaria deaths declined from 36.0/100,000 population in 1958 to 0.1/100,000 population in 2009. Diphtheria-related deaths decreased throughout the study period. In contrast, deaths from polio showed much year-to year variability, with a surge in 1975; however, polio-related deaths remained low ( 60 years of age (data not shown). During 1959–1968, mortality rates for sexually transmitted diseases dropped sharply. However, starting in the early 1970s, the rates increased for a decade before declining again (Figure 4). Discussion Our findings demonstrate a substantial decrease in deaths overall in Thailand from 1958 through 1986, followed by an increase beginning in 1987 and then a leveling-off beginning in the early 2000s. All-cause mortality rate trends were similar for males and females, but the rate was consistently higher for males. The gender gap in all-cause mortality rates among persons 25–44 years became more pronounced in recent years, mostly because of fatal traffic accidents and HIV/AIDS-related deaths among men, a group that was more affected by HIV/AIDS in the first phase of the epidemic ( 12 , 13 ). Age-specific mortality rates for children 0–4 years of age showed the greatest decline; the development of and equitable access to maternal and child health care services and vaccination may have contributed to this decline ( 14 , 15 ). The all-cause mortality rate for children 0–4 years of age declined over the study period; however, after the introduction of the Expanded Program on Immunization (EPI), the rate declined 28% (from 715 to 514 deaths /100,000 population). The extensive geographic coverage of primary health care services contributed significantly to maternal and child health outcomes ( 16 ). From 1958 through the mid-1990s, the infectious disease mortality rate in Thailand declined substantially, largely because of declines in malaria, TB, pneumonia, and gastrointestinal infection. Several factors contributed to this trend, including general improvements in sanitation, improved access to medical care (a result of health infrastructure expansions at the district level), and financial risk protection ( 16 ), and the introduction of routine childhood vaccination through EPI, which was officially launched in 1977 ( 14 ). Since 1987, coverage with TB, diphtheria-tetanus-pertussis, and tetanus toxoid vaccines has been 96%, 75%, and 60%, respectively ( 17 ). Deaths related to vaccine-preventable infectious disease declined sharply in association with >90% EPI coverage in the 1990s ( 18 ). In the United States, studies have shown a decline in infectious disease–related deaths during the twentieth century ( 5 , 6 ). In the late 1990s, the decreasing trend for the infectious disease–related deaths reversed. Disease categories that contributed most to this reversal were HIV/AIDS, TB, and pneumonia; all of which had sharply elevated mortality rates during 1997–2003 and decreasing rates in 2004. HIV/AIDS emerged in Thailand in the mid-1980s and spread rapidly with devastating effects ( 19 ). In 1999 in Thailand, HIV/AIDS had become the leading cause of death in men 25–44 years of age, resulting in a widening gap in the mortality rate between men and women ( 8 , 13 ). Co-infection with TB and HIV is common; thus; the rising number of TB-related deaths during 1995–2003 coincided with the explosive epidemic of HIV infection and gradually led to the emergence of multidrug-resistant TB ( 20 , 21 ). Moreover, the reported incidences of pneumonia and pneumonia-related deaths had been increasing in Thailand since the mid-1980s ( 22 ). It is likely that HIV/AIDS contributed to the pneumonia-related mortality rate. However, this contribution was not readily apparent until later because HIV/AIDS was not a reportable cause of death until 1994 and because stigma was likely a barrier to reporting in the early years of the HIV/AIDs epidemic ( 23 ). Furthermore, if the code for opportunistic infectious diseases was used for deaths caused by HIV/AIDS, the number of deaths from HIV/AIDs may have been underestimated ( 10 , 24 ). In persons with HIV/AIDS in Southeast Asia, the common opportunistic infections were TB, cryptococcosis, and Pneumocystis carinii and Pennicillium marneffei fungal infections, all of which can cause pneumonia ( 25 ). The observed increase in pneumonia-related deaths in very elderly persons may also reflect the misclassification of the cause of death because pneumonia is often the immediate, rather than underlying, cause of death. A study to verify cause of death data found that ≈31% of deaths coded as being caused by pneumonia should have been classified as being caused by cerebrovascular disease, chronic obstructive pulmonary disease, diabetes, or genitourinary disease ( 10 ). We found that deaths from HIV/AIDS and TB declined during 2004–2009; this decline may account for the concurrent leveling-off of infectious disease–related mortality. Thailand implemented a national AIDS program in 1991 and a national antiretroviral (ARV) treatment program in 2000. The ARV treatment program was designed to increase access to health care and treatment, but it was not until 2004 that the universal ARV treatment program was fully implemented, providing ARV treatment for all eligible patients under the National Access to ARVs for People Living with HIV/AIDS program. As the program scaled up, universal ARV contributed significantly to the reduction in AIDS-related deaths ( 26 – 28 ). Two parallel prevention programs, vertical transmission prevention and condom promotion, contributed to decreasing the incidence of HIV infection and changed the epidemic in Thailand from one that was generalized to one that was concentrated in certain subpopulations, particularly injection-drug users, homosexual men, and youth. TB-related deaths were also reduced through early initiation of ARV treatment program for persons with HIV, implementation of DOTS (directly observed treatment, short course), and appropriate antimicrobial drug regimens for TB treatment ( 29 ). DOTS was implemented nationwide in Thailand in 2001, and since then, the country has achieved the international goal for detecting >70% of the estimated cases of infectious TB (i.e., cases in persons with a TB-positive sputum smear); however, Thailand has not met the international goal for successfully treating >85% of the detected cases ( 30 ). The main issues relating to TB control were the fragmented delivery of services; limited capacity of stakeholders and limited coordination between stakeholders; weak referral linkages between hospitals and health centers; high TB/HIV co-infection rates and limited access to ARV treatment, especially among poor persons and those with less education; unsupervised treatment with high default rates; and widespread unregulated use of second-line antimicrobial drugs, which could lead to an outbreak of multidrug-resistant TB and extensively drug-resistant TB ( 31 ). Certain infectious diseases (e.g., TB) are re-emerging, and emerging HIV/AIDS epidemics in certain subpopulations have considerable implications for the Thai population. Continued monitoring and evaluation of the effect of interventions on disease incidence and mortality rates are critical if the global goal of curing 85% of TB cases is to be achieved. We reviewed mortality rates during 1958–2009 in Thailand by using a standardized infectious disease classification scheme. Three possible artifacts in year-to-year fluctuations in the mortality rate over the study period should be considered. The first artifact concerns changes that were made to Thailand’s data recording system during the study period. Four versions of the ICD systems were used, and ICD code changes can lead to substantial changes in long-term trends in cause-specific mortality rates ( 32 ). Our results show an increasing trend in deaths from pneumonia and TB since 1994, when the switch was made from ICD-9 to ICD-10 coding; we have not accounted for the differences in diagnostic trends concurrent with the changes in coding. When a US National Center for Health Statistics comparability ratio was applied to the US mortality rates for influenza and pneumonia, it appeared that the declines mainly resulted from the introduction of the ICD-10 coding system ( 33 ). We did not apply comparability ratios in our analysis because such ratios were not developed with the data provided by the Thai MOPH. The second possible artifact is that deaths sharply declined from 1996 to 1997, and this decline was followed by a sharp increase from 1998 to 1999. We cannot rule out that such sudden changes may have resulted from changes in the process for reporting deaths, which was implemented in 1996. In the new death certification system, each death was entered into the computer database in the Civil Registration Database at the Bureau of Registration Administration of the MOI and then transferred to the vital registration database at the MOPH. The third possible artifact is the cause of death coding errors. The coding of polio deaths since 1997, is an example of such errors. The Polio Eradication Campaign in Thailand was started in 1990, and the last polio case was reported in April 1997 ( 34 ). Cases of and deaths from acute flaccid paralysis are aggressively investigated, making it unlikely that a single death could be missed. However, despite the lack of any reported cases of polio since 1997, a total of 274 polio-related deaths were coded during 1997–2009. In general, the quality of death statistics in Thailand is considered poor because many death registrations are incomplete and a large proportion have poorly defined causes of death ( 11 , 35 ). Furthermore, during the 1960s and 1970s, only ≈60% of deaths were registered. That percentage increased to 76% in the mid-1980s and to 95% in the mid-1990s. The highest proportion of unregistered deaths was for infants; this was a result of death occurring, in many cases, before the birth was registered ( 4 , 36 ). The proportion of in-hospital deaths increased from 20% during the 1980s to 43% in 2009 ( 37 ). The validity of the overall cause-of death statistics during that time is questionable because many out-of-hospital deaths were coded by persons not medically qualified to determine the cause of death. All of these factors may have influenced the study findings. This study has some possible limitations. The analysis was based on death attributed to the underlying cause of death as it was reported on death certificates and published in the Report of Public Health Statistics. Because death records list only one cause of death, we knew only the underlying cause of death and, thus, may have underestimated the effect of infectious diseases as a contributing cause of death. As a result, this study may underestimate the role of infectious diseases on mortality rates. In addition, the aggregate nature of our data prevented additional exploration of the specific cause of death by age group. Our estimate of the extent of infectious disease is conservative, focusing exclusively on deaths. This focus reflects only part of the effects from disease because infectious disease may result in substantial illness or disability, or both, without causing death. Future analyses of other dimensions of the effects of infectious diseases, such as their effect on the economy, the number of hospitalizations, and the number of life-years lost because of disability, will provide information to inform policy-making decisions. The implementation of a malaria control program and new and effective antimicrobial drugs for treating TB contributed considerably to the reduction in communicable disease–related illness and deaths in the second half of the twentieth century ( 1 , 38 – 40 ). The emergence of HIV/AIDS and the increase in TB- and pneumonia-related deaths in the late twentieth century dramatically interrupted the epidemiologic transition in Thailand. A universal ARV treatment program has rapidly scaled up and resulted in a decrease in the number of deaths from HIV/AIDS after 2003; however, this decline remains unstable. Recent trends emphasize the dynamic process of infectious diseases and highlight the need for sustained resources and efforts to combat their emergence or re-emergence. These data also highlight the importance of addressing health disparities between men and women. Reliable, relevant, and timely mortality data are crucial to guide effective policy responses to protect and promote population health.
                Bookmark

                Author and article information

                Journal
                Emerg Infect Dis
                Emerging Infect. Dis
                EID
                Emerging Infectious Diseases
                Centers for Disease Control and Prevention
                1080-6040
                1080-6059
                November 2012
                : 18
                : 11
                : 1922-1923
                Affiliations
                Author affiliation: Centers for Disease Control and Prevention, Atlanta, Georgia, USA
                Author notes
                Address for correspondence: Polyxeni Potter, EID Journal, Centers for Disease Control and Prevention, 1600 Clifton Rd NE, Mailstop D61, Atlanta, GA 30333, USA; email: pmp1@ 123456cdc.gov
                Article
                AC-1811
                10.3201/eid1811.AC1811
                3559178
                23092653
                Categories
                About the Cover
                About the Cover

                Comments

                Comment on this article