Warning: mkdir(): Permission denied in /home/virtual/lib/view_data.php on line 81

Warning: fopen(upload/ip_log/ip_log_2024-11.txt): failed to open stream: No such file or directory in /home/virtual/lib/view_data.php on line 83

Warning: fwrite() expects parameter 1 to be resource, boolean given in /home/virtual/lib/view_data.php on line 84
Spatiotemporal Clusters and Trends of Pneumocystis Pneumonia in Korea
| Home | E-Submission | Sitemap | Contact us |  
top_img
Korean J Parasito Search

CLOSE

Korean J Parasito > Volume 60(5):2022 > Article
Kim, Nam, Ahn, Lee, and Kim: Spatiotemporal Clusters and Trends of Pneumocystis Pneumonia in Korea

Abstract

This study determined the recent status and trend of Pneumocystis jirovecii pneumonia (PcP) in the non-human immunodeficiency virus (HIV) (non-HIV-PcP) and HIV (HIV-PcP) infected populations using data from the Health Insurance Review & Assessment Service (HIRA) and the Korea Disease Control and Prevention Agency (KDCA). SaTScan and Joinpoint were used for statistical analyses. Non-HIV-PcP cases showed an upward trend during the study period from 2010 to 2021, with the largest number in 2021 (551 cases). The upward trend was similar until 2020 after adjusting for the population. Seoul had the highest number of cases (1,597) in the non-HIV-PcP group, which was the same after adjusting for the population (162 cases/1,000,000). It was followed by Jeju-do (89 cases/1,000,000). The most likely cluster (MLC) for the non-HIV-PCP group was Seoul (Relative Risk (RR)=4.59, Log Likelihood Ratio (LLR)=825.531), followed by Jeju-do (RR=1.59, LLR=5.431). An upward trend was observed among the non-HIV-PcP group in the Jeju-do/Jeollanam-do/Jeollabuk-do/Gyeongsangnam-do/Busan/Daejeon/Daegu/Ulsan joint cluster (29.02%, LLR=11.638, P<0.001) located in the southern part of Korea. Both women and men in the non-HIV groups showed an overall upward trend of PcP during the study period. Men in the 60–69 age group had the highest annual percentage change (APC 41.8) during 2014–2019. In contrast, the HIV groups showed a falling trend of PcP recently. Men in the 60–69 age group had the most decrease (APC −17.6) during 2018–2021. This study provides an analytic basis for health measures and a nationwide epidemiological surveillance system for the management of PcP.

INTRODUCTION

Pneumocystis jirovecii (formerly P. carinii) pneumonia (PcP) is an opportunistic respiratory infection in immunocompromised hosts, particularly those infected with the human immunodeficiency virus (HIV) and showing low CD4 T cell counts. Its incidence has decreased over the decades due to the use of highly efficient antiretroviral therapy and PcP prophylaxis [1,2]. However, it shows an upward trend in the general population with non-HIV immunocompromised status such as malignancy, organ transplants, and long-term use of immunosuppressants, and is a clinically significant disease [3]. The incidence of PcP in the general population is also increasing in Korea [4]. Hematologic malignancy was the highest underlying condition, and immunosuppressive therapies had highly significant association with PcP occurrence, but there are limitations to the study due to selection bias of hospital data. There are few studies on regional variance and temporal trends of PcP both in the general and HIV-infected populations for the entire region of Korea.
It is important to understand the regional and temporal trends of PcP incidence and prevalence to identify and provide evidence of epidemiological features of Korean patients with or without HIV infection, and to help customize medical guidelines and treatment strategies for the patients. This study determined the current disease status and most recent long-term trend (2010–2021) of PcP in the non-HIV and HIV groups to better understand its epidemiologic trends in Korea.

MATERIALS AND METHODS

Ethics statement

This study was performed under the regulation of the IRB Committee of The Catholic University of Korea (No. MIRB-20201127-002). This research adhered to the tenets of the Declaration of Helsinki.

Data source and definition

The nationwide PcP cases for 12 years (2010–2021) from 16 administrative districts in Korea were obtained from the Health Insurance Review & Assessment Service (HIRA) of Korea (https://opendata.hira.or.kr/home.do [cited 2022 July]) under the keyword “pneumocystis pneumonia”. The query returned “HIV disease resulting in Pneumocystis jirovecii pneumonia” (ICD-10 Version:2019, B206). Further query returned “pneumonia in parasitic diseases” (B59) and “pneumonia in P. jirovecii” (B485). The B206 cases were assigned to the PcP in HIV (HIV-PcP) group, and the B59 and B485 cases were assigned to the non-HIV PcP (non-HIV-PcP) group. The HIRA collects and connects all relevant data including heath information of all the patients across the country, and the accuracy and reliability of its data have been systemically validated [5].
The population data of the 16 administrative districts from 2010 to 2021 were obtained from the Korean Statistical Information Service (https://kosis.kr/index/index.do [cited 2022 May]). The geographical locations of the cases were set to the latitude and longitude of administrative center as the search point since the case data were made up according to administrative district unit. Average population of the districts were calculated for the full period to evaluate overall disease status. Non-HIV-PcP case numbers were adjusted for the district’s population (cases/1,000,000) in the corresponding year to enable comparison between the different districts (Table 1). Non-HIV-PcP case numbers were also adjusted for age and sex (cases/1,000,000) in the corresponding year (Table 2).
Although the HIRA data is nationwide, it is based on claims by healthcare services, therefore it might not be suitable for evaluating the disease status in chronic diseases as multiple reimbursements can be claimed. HIV itself has mainly become a controllable chronic disease, therefore, a new database for an HIV population was required for evaluating the PcP in HIV cases. Annual HIV infectious status for 2010 to 2021 were extracted from the “Annual Report on the Notified HIV/AIDS in Korea”, which was obtained from the Infectious Disease Portal of the Korea Disease Control and Prevention Agency (KDCA: https://www.kdca.go.kr/npt/biz/npp/portal/nppPblctDtaMain.do [cited 2022 July]). HIV-PcP case numbers were adjusted for the HIV population (cases/1,000) in the corresponding year to enable comparison between the different age and sex groups (Table 3).

Spatiotemporal analyses of clusters and trend

SaTScan (v10.0) [6] was used to identify clusters and evaluate their significance through simulation. This was only possible for the non-HIV group, as the HIV annual report had no data on location. The discrete Poisson model was used since the case data was associated with the background population at risk. Spatial scan statistic is known to work the best for detecting spatial clusters and can be effective for a small number of case studies, such as rare outbreaks and help to find appropriate setting for cluster size [79].
SaTScan creates a circular window on the map and scans the study area by varying the window size to detect clusters with highest likelihood ratio. The window size determines a percentage of the population at risk within its boundaries [10]. Various studies have been performed to address this issue, and SaTScan has been progressively updated to address these results and implemented them on the new versions [11,12]. In this study, a window size of 50% was used to enable detection of the significant clusters.
General trend of the disease according to administrative districts was determined through spatial variation in temporal trend analysis, by scanning for clusters with either increasing or decreasing rates. The Monte Carlo simulations with an inference of 9,999 was used to evaluate the statistical significance of the clusters [13]. A significance level of α<0.05 was used as a standard. QGIS software (v3.16) was used to visualize cluster patterns on a map. The clusters and trends are shown in order of log likelihood ratio (LLR).

Trend analysis

PcP trend for both non-HIV and HIV groups, according to sex and age, was determined using Joinpoint Regression Program from the National Cancer Institute website (v4.9.1.0) (https://surveillance.cancer.gov/joinpoint/) [14,15]. The present study used crude rates, computed by the Joinpoint software, which is expressed as the number of cases for a given population at risk. A maximum number of 2 joinpoint was used, making it possible to see whether the incidence is better explained by a single trend or by the existence of multiple trend segments during the study period. Briefly, joinpoint regression identifies the best-fitting breakpoints (years), in which there was a significant change in the incidence rate (crude rates) [16]. The results were summarized as annual percentage changes (APC) with the best model fit for each trend segment. Statistical significance was calculated with an inference of 9,999 and expressed as P-value. A significance level of α<0.05 was used as a standard. The results were also output in graphs by the software. The final selected model from statistically significant age groups according to sex was output into a single graph to view multiple models simultaneously. These graphs were then recreated for enhanced legibility using the output data.

RESULTS

General characteristics

The non-HIV-PcP cases showed an upward trend during the study period of 2010 to 2021, with the largest number of cases in 2021 (551 cases). Adjusted PcP infection rate followed a similar trend, increasing through 2020 and then decreasing to some extents thereafter. Seoul had the highest number of cases (1,597) of PcP, followed by Gyeonggi-do (560). The highest number of adjusted cases was also observed in Seoul after adjusting for the population (162 cases/1,000,000) (Table 1). Interestingly, Jeju-do had the second highest number of adjusted cases after adjusting for the population (89 cases/1,000,000).
In the non-HIV-PcP age groups, the 60–69 and 70–79 age groups in women showed the highest average cases of PcP (24.4 and 21.2/year, respectively). Similarly, 60–69 and 70–79 age groups in men showed the highest average cases (40.8 and 39.3/year, respectively). After adjusting for the population (cases/1,000,000), women and men in the 70–79 age group had the highest adjusted cases (11.0 and 25.5/year, respectively). Men tended to have a higher crude rate of PcP, but it continued to increase with some fluctuation in both men and women (Table 2).
In the HIV-PcP age groups, the 60–69 and 50–59 age groups in women showed the highest average cases of PcP (4.4 and 4.2/year, respectively). In contrast, the 40–49 and 30–39 age groups in men showed the highest average cases of PcP (78.6 and 67.5/year, respectively). After adjusting for the corresponding HIV case numbers (cases/1,000), women in the 60–69 and men in the 40–49 age groups had the highest average adjusted cases of PcP (32.1 and 29.8, respectively). Men also tended to have a higher crude rate of PcP in the HIV-PcP group, but it peaked around 2017–2018, and continued to decrease steadily in both men and women (Table 3).

Pure spatial analysis for clusters and spatial variation in temporal trends by districts

When regional cluster analysis was performed for the non-HIV-PcP group, the most likely cluster (MLC) for PcP was Seoul with a relative risk (RR) and log likelihood ratio (LLR) of 4.59 and 825.231, respectively. The Jeju-do cluster also had a high RR (1.59) and LLR (5.431) of non-HIV-PcP (Fig. 1; Table 4).
Spatiotemporal trends analysis showed an upward trend among the non-HIV-PcP group in the Jeju-do/Jeollanam-do/Jeollabuk-do/Gyeongsangnam-do/Busan/Daejeon/Daegu/Ulsan joint cluster (29.02%, LLR=11.638, P<0.001) that is mostly located in the southern part of Korea (Fig. 2; Table 5). Gangwon-do also showed an upward trend, but was not significant.

Trends of PcP in age groups according to sex in both non-HIV and HIV groups

Change in crude rate of PcP in non-HIV and HIV groups according to sex and age are shown in Fig. 3. In the non-HIV-PcP group, women in the 40 and over age groups showed significant upward trends of PcP throughout the study period. In contrast, men showed different trends according to age. The 30–59, 70 years and over age groups in men showed significant upward trends during the entire study period (trend 1). The 20–29 age group showed an upward trend, but was not significant during 2010–2015 (trend 1) and 2015–2018 (trend 2), but fell afterwards (trend 3) with an annual percentage change (APC) of −46.8 (P=0.045). The 60–69 age group showed significant upward trend only during 2014–2019 (trend 2, APC 41.8, P<0.001) (Fig. 3; Table 6).
Falling trends of PcP were observed mainly in the relatively younger age groups living with HIV (HIV-PcP). This was in contrast to the non-HIV-PcP group, which showed overall upward trends of PcP in all age groups. The 20–29 age group in women showed significant upward trend of PcP until 2016, and then fell continuously to 2021, but it was not significant. On the other hand, the 50–59 age group in women showed significant decrease of PcP during the entire study period. Men in the HIV-PcP group showed varying trends for most age groups. The 20–29 age group showed a falling trend from 2012 to 2021 (trend 2, APC −11.6, P<0.01). The 30–39 age group showed a sharp increasing rate until 2015 (trend 1, APC 13.2, P=0.02), but fell afterwards significantly (trend 2, APC −12.6, P<0.01). The 40–49 age group showed a falling trend from 2015 to 2021 (trend 2, APC −5.7, P<0.01), while the 60–69 age group showed a more prominent fall during 2018–2021 (trend 2, APC −17.6, P<0.01) (Fig. 3; Table 6).

DISCUSSION

The purpose of the present study was to evaluate the latest PcP status, and whether there have been changes in temporal trends from 2010 to 2021 in Korea. Although there have been previous studies on the prevalence and incidence of PcP in Korea, this study is significant in that it provides statistically more recent data from the entire Korean population [17,18]. We separately assessed PcP cases in the non-HIV and the HIV groups, since PcP occurs more frequently in the immunocompromised individuals [3].
In the non-HIV group, Seoul, the capital city of Korea where almost a quarter of the Korean population live, had the highest number of PcP cases. Furthermore, Seoul was the major cluster for PcP during the study period. Medical resources are densely concentrated in Seoul facilitating the development of diagnostic and treatment measures for individuals with rare, or incurable disease such as solid organ or hematopoietic cell transplantation [19]. Advanced health care facilities and providers in the major city may have contributed to the increasing PcP diagnostic rate in the non-HIV group.
Pneumocystis is air-borne and transmitted from human to human [20,21]. It can colonize in the immunocompetent people, roam from individual to individual, and then may develop PcP when the host become immunocompromised, or if it encounters an immunocompromised human host [22]. Thus, an immunocompetent human host could serve as a reservoir of Pneumocystis, and its transmission is augmented when individuals are close enough to each other [23]. These transmission characteristics of Pneumocystis may explain the high number of cases of PcP in densely populated districts such as Seoul and Gyeonggi-do.
Gyeonggi-do, which is the second largest district of Korea, showed the second highest number of PcP cases, but we found that in the non-HIV-PcP group, Jeju-do has the second highest PcP rate after adjusting for the population; it was also the second largest cluster. PcP incidence tends to be relatively high in non-HIV immunocompromised patients who are using advanced medical resources in large cities. Environmental factors such as temperature, humidity, and the scale of green space may provide evidence supporting the association with an increased incidence of non-HIV-PcP. Jeju-do is an island at the southern part of Korea characterized by warm weather and high humidity. These factors may play a role in becoming the second likely cluster for PcP. Studies have shown that PcP cases are mainly found during outdoor activities such as hiking, camping, and gardening in affluent greenery where Pneumocystis has a high potential to spread airborne exposure to a human [24]. Peak incidence of PcP were correlated with climatic factors such as warm temperature and high humidity contributing to the high burden of Pneumocystis in air [25,26].
Non-HIV-PcP showed an increasing tendency in districts mainly located in the southern part of Korea, which is consistent with studies showing that PcP is mainly diagnosed more in regions with a warm weather [25,26]. Other than the climatic and regional factors associated with the southern districts of Korea, lack of awareness for PcP prophylaxis in non-HIV immunocompromised patients seems to contribute to an increase in the overall incidence and prevalence in the non-HIV-PcP group [27]. The guideline for prophylaxis against PcP in the HIV infected population is rather clear, which is based on the CD4 count, but the range for prophylaxis against PcP is broad and varied in non-HIV immunocompromised individuals, such as rheumatic diseases, inflammatory bowel diseases, malignancies, and solid organ transplant recipients [2830]. The increase in organ transplantation appears to increase in the PcP incidence of non-HIV individuals. The number of transplantations of various human organs and tissues has been growing for several decades with the advances of medical resources such as transplant techniques and immunosuppressants [31]. Although Seoul has the highest number of transplantations, these advances appear to be nationwide including the southern districts of Korea.
PcP cases increased in the older age groups in both men and women among the non-HIV-PcP group during the study period, suggesting these age groups are at a high risk for PcP due to immunosenescence, which is described by a progressive deterioration of the immune system related to aging [32]. The reduced ability of the immune system in this population might provoke further diseases that aggravate the immunocompromised conditions, leading to higher mortality [3234]. In addition to the issue of declined immune function in the elderly, whether chemoprophylaxis for PcP was performed on the immunocompromised individuals or not, appears to reflect the opposite temporal trends observed between the non-HIV-PcP and HIV-PcP groups [3537]. Recent studies have shown that PcP incidence is globally decreasing due to the early use of effective antiviral agents to treat HIV, followed by careful monitoring and management for their health status including PcP prophylaxis [38,39]. Thus, the incidence of PcP is rising and the elderly are at high risk, so extending the range of prophylaxis against PcP should be required to lower the mortality due to PcP in the non-HIV group.
Although a downward trend was observed in the HIV-PCP group, men tended to have a higher incidence than women. This tendency might be due to the HIV infection status itself, and not to the sexual predilection of Pneumocystis. It is similar to the studies that have shown specific genotypes of Pneumocystis have strong correlation with the underlying diseases or conditions of the human host that caused the immunocompromised status [40]. Additionally, various genotypes of Pneumocystis based on the status of HIV infection itself and/or the underlying health conditions, including any combined complications, in people living with HIV have been reported, supporting genetic epidemics of Pneumocystis [4143]. Although the genetic epidemics of Pneumocystis may not be representative of a link with PcP incidence, it may be helpful in predicting PcP occurrence in Korea.
We excluded the regional cluster and trend analysis for the HIV-PcP group in this study. The HIRA resource, which we analyzed, is a data claimed by clinics or hospitals that may be in regions different from that of the individual’s actual address, so there is a limit to reflecting the regionality, especially for people who live with HIV. They may not visit a local healthcare provider where they live, expecting treatment to be refused due to self-imposed discrimination stemming from social stigma, which may lead to behaviors such as remaining anonymous, using false identification, leaving home, and moving to other regions for treatment [44,45].
HIV infection in Korea has been declining since first reported back in 1985, and PcP has been studied as one of its opportunistic infections in the past [4648]. However, it has been vigorously studied in non-HIV immunocompromised patients such as those with rheumatic diseases, auto-immune diseases, and transplantation recipients [4952]. Our study revealed the status and trend of PcP in Korea. i) The PcP of the non-HIV population depends on regional environmental and climatic conditions as observed in Jeju-do and the southern parts of Korea, ii) the high risk of elderly, and iii) reinforcing studies based on data from tertiary-care hospitals showing similar trends in PcP over a decade in both the non-HIV and the HIV groups [17]. This study provides an analytic basis for health measures and a nationwide epidemiological surveillance system for the prevention of PcP.

Conflict of interest

The authors declare no conflict of interest related to this study.

REFERENCES

1. Grimwade K, Swingler G. Cotrimoxazole prophylaxis for opportunistic infections in children with HIV infection. Cochrane Database Syst Rev 2003;CD003508 https://doi.org/10.1002/14651858.CD003508
crossref pmid
2. Kaplan JE, Hanson D, Dworkin MS, Frederick T, Bertolli J, Lindegren ML, Holmberg S, Jones JL. Epidemiology of human immunodeficiency virus-associated opportunistic infections in the United States in the era of highly active antiretroviral therapy. Clin Infect Dis 2000;30:suppl. 5-14 https://doi.org/10.1086/313843
crossref pmid
3. Morris A, Lundgren JD, Masur H, Walzer PD, Hanson DL, Frederick T, Huang L, Beard CB, Kaplan JE. Current epidemiology of Pneumocystis pneumonia. Emerg Infect Dis 2004;10:1713-1720 https://doi.org/10.3201/eid1010.030985
crossref pmid pmc
4. Lee HY, Choi SH, Kim T, Chang J, Kim SH, Lee SO, Kim MN, Sung H. Epidemiologic trends and clinical features of Pneumocystis jirovecii Pneumonia in Non-HIV patients in a Tertiary-Care Hospital in Korea over a 15-year-period. Jpn J Infect Dis 2019;72:270-273 https://doi.org/10.7883/yoken.JJID.2018.400
crossref pmid
5. Seo HJ, Kim SY, Lee YJ, Jang BH, Park JE, Sheen SS, Hahn SK. A newly developed tool for classifying study designs in systematic reviews of interventions and exposures showed substantial reliability and validity. J Clin Epidemiol 2016;70:200-205 https://doi.org/10.1016/j.jclinepi.2015.09.013
crossref pmid
6. Kulldorff M. A spatial scan statistic. Commun Stat-Theor M 1997;26:1481-1496 https://doi.org/10.1080/03610929708831995
crossref
7. Stelling J, Yih WK, Galas M, Kulldorff M, Pichel M, Terragno R, Tuduri E, Espetxe S, Binsztein N, O’Brien TF, Platt R. Automated use of WHONET and SaTScan to detect outbreaks of Shigella spp. using antimicrobial resistance phenotypes. Epidemiol Infect 2010;138:873-883 https://doi.org/10.1017/s0950268809990884
crossref pmid pmc
8. Mathes RW, Lall R, Levin-Rector A, Sell J, Paladini M, Konty KJ, Olson D, Weiss D. Evaluating and implementing temporal, spatial, and spatio-temporal methods for outbreak detection in a local syndromic surveillance system. PLoS One 2017;12:e0184419 https://doi.org/10.1371/journal.pone.0184419
crossref pmid pmc
9. Chen J, Roth RE, Naito AT, Lengerich EJ, Maceachren AM. Geovisual analytics to enhance spatial scan statistic interpretation: an analysis of U.S. cervical cancer mortality. Int J Health Geogr 2008;7:57-74 https://doi.org/10.1186/1476-072X-7-57
crossref pmid pmc
10. Kulldorff M, Nagarwalla N. Spatial disease clusters: detection and inference. Stat Med 1995;14:799-810 https://doi.org/10.1002/sim.4780140809
crossref pmid
11. Wang W, Zhang T, Yin F, Xiao X, Chen S, Zhang X, Li X, Ma Y. Using the maximum clustering heterogeneous set-proportion to select the maximum window size for the spatial scan statistic. Sci Rep 2020;10:4900-4913 https://doi.org/10.1038/s41598-020-61829-y
crossref pmid pmc
12. Yoo H, Jung I. Optimizing the maximum reported cluster size for normal-based spatial scan statistics. CSAM 2018;25:373-383 https://doi.org/10.29220/CSAM.2018.25.4.373
crossref
13. Azage M, Kumie A, Worku A, Bagtzoglou AC. Childhood diarrhea exhibits spatiotemporal variation in northwest Ethiopia: a SaTScan spatial statistical analysis. PLoS One 2015;10:e0144690 https://doi.org/10.1371/journal.pone.0144690
crossref pmid pmc
14. Clegg LX, Hankey BF, Tiwari R, Feuer EJ, Edwards BK. Estimating average annual per cent change in trend analysis. Stat Med 2009;28:3670-82 https://doi.org/10.1002/sim.3733
crossref pmid pmc
15. Kim HJ, Fay MP, Feuer EJ, Midthune DN. Permutation tests for joinpoint regression with applications to cancer rates. Stat Med 2000;19:335-351 https://doi.org/10.1002/(sici)1097-0258(20000215)19:3<335::aid-sim336>3.0.co;2-z
crossref pmid
16. Molnar A, Iancu M, Radu R, Borzan CM. A joinpoint regression analysis of syphilis and gonorrhea incidence in 15–19-year old adolescents between 2005 and 2017: a regional study. Int J Environ Res Public Health 2020;17:5385-5396 https://doi.org/10.3390/ijerph17155385
crossref pmid pmc
17. Lee HY, Choi SH, Kim T, Chang J, Kim SH, Lee SO, Kim MN, Sung H. Epidemiologic trends and clinical features of Pneumocystis jirovecii pneumonia in non-HIV Patients in a Tertiary-Care Hospital in Korea over a 15-Year-Period. Jpn J Infect Dis 2019;72:270-273 https://doi.org/10.7883/yoken.JJID.2018.400
crossref pmid
18. Choi Y, Choi BY, Kim SM, Kim SI, Kim J, Choi JY, Kim SW, Song JY, Kim YJ, Park DW, Kim HY, Choi HJ, Kee MK, Shin YH, Yoo M. Epidemiological characteristics of HIV infected Korean: Korea HIV/AIDS Cohort Study. Epidemiol Health 2019;41:e2019037 https://doi.org/10.4178/epih.e2019037
crossref pmid pmc
19. Affairs KIFHaS. Health and Medical Resources Survey [internet]; [cited 2022 May 25]. Available from: https://www.kihasa.re.kr/ (in Korean)

20. Vera C, Rueda ZV. Transmission and colonization of Pneumocystis jirovecii. J Fungi (Basel) 2021;7:979-994 https://doi.org/10.3390/jof7110979
crossref pmid pmc
21. Chabé M, Durand-Joly I, Dei-Cas E. Transmission of Pneumocystis infection in humans. Med Sci (Paris) 2012;28:599-604 (in French). https://doi.org/10.1051/medsci/2012286012
crossref pmid
22. Gigliotti F, Harmsen AG, Wright TW. Characterization of transmission of Pneumocystis carinii f. sp. muris through immunocompetent BALB/c mice. Infect Immun 2003;71:3852-3856 https://doi.org/10.1128/IAI.71.7.3852-3856.2003
crossref pmid pmc
23. Dumoulin A, Mazars E, Seguy N, Gargallo-Viola D, Vargas S, Cailliez JC, Aliouat EM, Wakefield AE, Dei-Cas E. Transmission of Pneumocystis carinii disease from immunocompetent contacts of infected hosts to susceptible hosts. Eur J Clin Microbiol Infect Dis 2000;19:671-678 https://doi.org/10.1007/s100960000354.
crossref pmid
24. Sokulska M, Kicia M, Wesolowska M, Hendrich AB. Pneumocystis jirovecii--from a commensal to pathogen: clinical and diagnostic review. Parasitol Res 2015;114:3577-3585 https://doi.org/10.1007/s00436-015-4678-6
crossref pmid pmc
25. Miller RF, Evans HER, Copas AJ, Cassell JA. Climate and genotypes of Pneumocystis jirovecii. Clin Microbiol Infect 2007;13:445-448 https://doi.org/10.1111/j.1469-0691.2006.01641.x
crossref pmid
26. Walzer PD. The ecology of pneumocystis: perspectives, personal recollections, and future research opportunities. J Eukaryot Microbiol 2013;60:634-645 https://doi.org/10.1111/jeu.12072
crossref pmid pmc
27. Dunbar A, Schauwvlieghe A, Algoe S, van Hellemond JJ, Reynders M, Vandecasteele S, Boelens J, Depuydt P, Rijnders B. Epidemiology of Pneumocystis jirovecii pneumonia and (non-)use of prophylaxis. Front Cell Infect Microbiol 2020;10:224-230 https://doi.org/10.3389/fcimb.2020.00224
crossref pmid pmc
28. Andreasen PB, Rezahosseini O, Moller DL, Wareham NE, Thomsen MT, Houmami R, Knudsen AD, Knudsen J, Kurtzhals JAL, Rostved AA, Pedersen CR, Rasmussen A, Nielsen SD. Pneumocystis jirovecii pneumonia in liver transplant recipients in an era of routine prophylaxis. Immun Inflamm Dis 2022;10:93-100 https://doi.org/10.1002/iid3.546
crossref pmid pmc
29. Chan SCW, Chung HY, Lau CS, Li PH. Epidemiology, mortality and effectiveness of prophylaxis for Pneumocystis jiroveci pneumonia among rheumatic patients: a territory-wide study. Ann Clin Microbiol Antimicrob 2021;20:78-84 https://doi.org/10.1186/s12941-021-00483-2
crossref pmid pmc
30. Pruett TL. Pneumocystis jirovecii: the changing landscape for prophylaxis. Transplantation 2021;105:2142-2143 https://doi.org/10.1097/TP.0000000000003577
crossref pmid
31. National Institute of Organ, Tissue, Blood Management. Organ Transplantation and Human Tissue Donation Statistics Annual Report 2020; National Institute of Organ, Tissue, Blood Management; Seoul, Korea (in Korean): Available from: https://www.konos.go.kr/board/boardListPage.do?page=sub4_2_1&boardId=30

32. Oh SJ, Lee JK, Shin OS. Aging and the immune system: the impact of immunosenescence on viral infection, immunity and vaccine immunogenicity. Immune Netw 2019;19:e37 https://doi.org/10.4110/in.2019.19.e37
crossref pmid pmc
33. Bajaj V, Gadi N, Spihlman AP, Wu SC, Choi CH, Moulton VR. Aging, immunity, and COVID-19: how age influences the host immune response to coronavirus infections? Front Physiol 2020;11:571416 https://doi.org/10.3389/fphys.2020.571416
crossref pmid pmc
34. Hong H, Wang Q, Li J, Liu H, Meng X, Zhang H. Aging, cancer and immunity. J Cancer 2019;10:3021-3027 https://doi.org/10.7150/jca.30723
crossref pmid pmc
35. Green H, Paul M, Vidal L, Leibovici L. Prophylaxis of Pneumocystis pneumonia in immunocompromised non-HIV-infected patients: systematic review and meta-analysis of randomized controlled trials. Mayo Clin Proc 2007;82:1052-1059 https://doi.org/10.4065/82.9.1052
crossref pmid
36. Lin X, Garg S, Mattson CL, Luo Q, Skarbinski J. Prescription of Pneumocystis Jiroveci pneumonia prophylaxis in HIV-infected patients. J Int Assoc Provid AIDS Care 2016;15:455-458 https://doi.org/10.1177/2325957416667486
crossref pmid pmc
37. Stern A, Green H, Paul M, Vidal L, Leibovici L. Prophylaxis for Pneumocystis pneumonia (PCP) in non-HIV immunocompromised patients. Cochrane Database Syst Rev 2014;CD005590 https://doi.org/10.1002/14651858.CD005590.pub3
crossref pmid
38. Radhi S, Alexander T, Ukwu M, Saleh S, Morris A. Outcome of HIV-associated Pneumocystis pneumonia in hospitalized patients from 2000 through 2003. BMC Infect Dis 2008;8:118-127 https://doi.org/10.1186/1471-2334-8-118
crossref pmid pmc
39. Huang L, Hecht FM, Stansell JD, Montanti R, Hadley WK, Hopewell PC. Suspected Pneumocystis carinii pneumonia with a negative induced sputum examination. Is early bronchoscopy useful? Am J Respir Crit Care Med 1995;151:1866-1871 https://doi.org/10.1164/ajrccm.151.6.7767533
crossref
40. Sokulska M, Kicia M, Wesolowska M, Piesiak P, Kowal A, Lobo ML, Kopacz Z, Hendrich AB, Matos O. Genotyping of Pneumocystis jirovecii in colonized patients with various pulmonary diseases. Med Mycol 2018;56:809-815 https://doi.org/10.1093/mmy/myx121
crossref pmid
41. Asai N, Motojima S, Ohkuni Y, Matsunuma R, Nakashita T, Kaneko N, Mikamo H. Pathophysiological mechanism of non-HIV Pneumocystis jirovecii pneumonia. Respir Investig 2022;60:522-530 https://doi.org/10.1016/j.resinv.2022.04.002
crossref pmid
42. Xue T, Du WQ, Dai WJ, Li YS, Wang SF, Wang JL, Zhang XR. Genetic polymorphisms of Pneumocystis jirovecii in HIV-positive and HIV-negative patients in northern China. Pol J Microbiol 2022;71:27-34 https://doi.org/10.33073/pjm-2022-002
crossref pmid pmc
43. Alanio A, Gits-Muselli M, Guigue N, Desnos-Ollivier M, Calderon EJ, Di Cave D, Dupont D, Hamprecht A, Hauser PM, Helweg-Larsen J, Kicia M, Lagrou K, Lengerova M, Matos O, Melchers WJG, Morio F, Nevez G, Totet A, White LP, Bretagne S. Diversity of Pneumocystis jirovecii across Europe: a multicentre observational study. EBioMedicine 2017;22:155-163 https://doi.org/10.1016/j.ebiom.2017.06.027
crossref pmid pmc
44. Mahajan AP, Sayles JN, Patel VA, Remien RH, Sawires SR, Ortiz DJ, Szekeres G, Coates TJ. Stigma in the HIV/AIDS epidemic: a review of the literature and recommendations for the way forward. AIDS 2008;22:suppl. 67-79 https://doi.org/10.1097/01.aids.0000327438.13291.62
crossref pmid pmc
45. Fauk NK, Hawke K, Mwanri L, Ward PR. Stigma and discrimination towards people living with HIV in the context of families, communities, and healthcare settings: a qualitative study in Indonesia. Int J Environ Res Public Health 2021;18:5424-5440 https://doi.org/10.3390/ijerph18105424
crossref pmid pmc
46. Kim JM, Kim NJ, Choi JY, Chin BS. History of Acquired Immune Deficiency Syndrome in Korea. Infect Chemother 2020;52:234-244 https://doi.org/10.3947/ic.2020.52.2.234.
crossref pmid pmc
47. Oh MD, Park SW, Kim HB, Kim US, Kim NJ, Choi HJ, Shin DH, Lee JS, Choe K. Spectrum of opportunistic infections and malignancies in patients with human immunodeficiency virus infection in South Korea. Clin Infect Dis 1999;29:1524-1528 https://doi.org/10.1086/313516.
crossref pmid
48. Kim JM, Cho GJ, Hong SK, Chang KH, Chung JS, Choi YH, Song YG, Huh A, Yeom JS, Lee KS, Choi JY. Epidemiology and clinical features of HIV infection/AIDS in Korea. Yonsei Med J 2003;44:363-370 https://doi.org/10.3349/ymj.2003.44.3.363
crossref pmid
49. Nam K, Park SH, Lee J, Jo S, Kim SO, Noh S, Park JC, Kim JY, Kim J, Ham NS, Oh EH, Song EM, Hwang SW, Yang DH, Ye BD, Byeon JS, Myung SJ, Yang SK. Incidence and risk factors of Pneumocystis jirovecii pneumonia in Korean patients with inflammatory bowel disease. J Gastroenterol Hepatol 2020;35:218-224 https://doi.org/10.1111/jgh.14832
crossref pmid
50. Lee G, Koo TY, Kim HW, Lee DR, Lee DW, Oh J, Kim BS, Kim MS, Yang J; Kotry Study Group. Comparison of early and late Pneumocystis jirovecii pneumonia in kidney transplant patients: the Korean Organ Transplantation Registry (KOTRY) Study. Sci Rep 2022;12:10682-10692 https://doi.org/10.1038/s41598-022-14580-5
crossref pmid pmc
51. Kim YJ, Woo JH, Kim MJ, Park DW, Song JY, Kim SW, Choi JY, Kim JM, Han SH, Lee JS, Choi BY, Lee JS, Kim SS, Kee MK, Kang MW, Kim SI. Opportunistic diseases among HIV-infected patients: a multicenter-nationwide Korean HIV/AIDS cohort study, 2006 to 2013. Korean J Intern Med 2016;31:953-960 https://doi.org/10.3904/kjim.2014.322
crossref pmid pmc
52. Choi EY, Kim JO, Kim YS, Yoon HJ, Jun JB, Sung YK. A case of Pneumocystis Jirovecii pneumonia in a patient with rheumatoid arthritis. J Rheum Dis 2012;19:359-363 (in Korean). https://doi.org/10.4078/jrd.2012.19.6.359
crossref

Fig. 1
Regional clusters detected for non-HIV-PcP cases. Light to dark gradient represents increasing order of log likelihood ratio. Area codes represent administrative districts of the Korean government. SE, Seoul; BU, Busan; IN, Incheon; DG, Daegu; GW, Gwangju; DJ, Daejeon; UL, Ulsan; GY, Gyeonggi-do; GA, Gangwon-do; CB, Chungcheongbuk-do; CN, Chungcheongnam-do; JB, Jeollabuk-do; JN, Jeollanam-do; GB, Gyeongsangbuk-do; GN, Gyeongsangnam-do; JE, Jeju-do.
kjp-60-5-327f1.jpg
Fig. 2
Spatiotemporal trend analysis of non-HIV-PcP cases for 2012–2020. Blue districts represent a joint cluster with an increasing trend of PcP. Area codes represent administrative districts of the Korean government. SE, Seoul; BU, Busan; IN, Incheon; DG, Daegu; GW, Gwangju; DJ, Daejeon; UL, Ulsan; GY, Gyeonggi-do; GA, Gangwon-do; CB, Chungcheongbuk-do; CN, Chungcheongnam-do; JB, Jeollabuk-do; JN, Jeollanam-do; GB, Gyeongsangbuk-do; GN, Gyeongsangnam-do; JE, Jeju-do.
kjp-60-5-327f2.jpg
Fig. 3
Trend analysis for PcP in non-HIV and HIV groups according to age and sex. (A) Non-HIV female 40 and over age groups show significant increase of PcP. (B) Non-HIV male 20–29 age group shows significant decrease during the third trend (2018–2021). The remaining age groups show significant increase of PcP during the study period. (C) HIV female 20–29 age group shows significant increase of PcP during the first trend (2010–2016). The 50–59 age group shows significant decrease of PcP. (D) HIV male 30–39 age group shows significant increase of PcP until peaking in 2015, and then decreases significantly. Age groups 20–29, 40–49 and 60–69 show significant decrease of PcP in the second trend (2012–2021, 2015–2021, and 2018–2021, respectively). Only age groups with significant trends are shown. Crude rates are calculated by mid-year in the Joinpoint software. Joinpoint graphs have been recreated for enhanced legibility using the output data. Dashed lines represent trends that are not significant.
kjp-60-5-327f3.jpg
Table 1
Total number of PcP cases in non-HIV group for 2010–2021 according to districts
Districtsa Average population Non-HIV-PcP cases
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 Total
SE 9,957,275 33 41 69 71 65 103 145 168 184 211 235 272 1,597
BU 3,482,081 4 5 2 6 3 3 13 11 8 37 33 27 152
IN 2,900,520 6 6 4 2 3 1 3 1 14 16 13 18 87
DG 2,472,552 1 5 2 1 6 4 10 5 21 27 20 24 126
GW 1,462,398 2 2 4 2 3 6 3 8 16 5 9 5 65
DJ 1,502,065 0 2 0 1 5 1 4 7 4 12 12 15 63
UL 1,150,344 0 0 3 0 0 2 5 4 11 2 8 10 45
GY 12,652,697 5 17 27 31 20 27 53 36 55 72 91 126 560
GA 1,542,329 1 4 1 2 2 3 4 0 6 12 12 12 59
CB 1,583,105 1 1 0 0 0 0 3 1 5 3 6 1 21
CN 2,091,409 0 0 3 3 3 4 4 3 5 9 4 3 41
JB 1,849,723 3 3 1 4 1 2 2 2 5 9 15 10 57
JN 1,891,733 1 0 0 0 0 3 0 0 0 2 1 3 10
GB 2,682,611 1 0 1 0 0 1 0 1 5 1 1 1 12
GN 3,342,717 2 2 2 3 3 4 5 9 6 19 13 15 83
JE 628,744 0 1 1 0 1 3 2 7 7 13 15 9 59
Total 60 89 120 126 115 167 256 263 352 450 488 551 3,037
Adjusted non-HIV-PcP casesb
SE 3 4 7 7 6 10 15 17 19 22 24 28 162
BU 1 1 1 2 1 1 4 3 2 11 10 8 45
IN 2 2 1 1 1 0 1 0 5 5 4 6 28
DG 0 2 1 0 2 2 4 2 9 11 8 10 51
GW 1 1 3 1 2 4 2 5 11 3 6 3 42
DJ 0 1 0 1 3 1 3 5 3 8 8 10 43
UL 0 0 3 0 0 2 4 3 10 2 7 9 40
GY 0 1 2 3 2 2 4 3 4 5 7 9 42
GA 1 3 1 1 1 2 3 0 4 8 8 8 40
CB 1 1 0 0 0 0 2 1 3 2 4 1 15
CN 0 0 1 1 1 2 2 1 2 4 2 1 17
JB 2 2 1 2 1 1 1 1 3 5 8 6 33
JN 1 0 0 0 0 2 0 0 0 1 1 2 7
GB 0 0 0 0 0 0 0 0 2 0 0 0 2
GN 1 1 1 1 1 1 1 3 2 6 4 4 26
JE 0 2 2 0 2 5 3 11 10 19 22 13 89
Total 13 21 24 20 23 35 49 55 89 112 123 118 682

a District codes: SE, Seoul; BU, Busan; IN, Incheon; DG, Daegu; GW, Gwangju; DJ, Daejeon; UL, Ulsan; GY, Gyeonggi-do; GA, Gangwon-do; CB, Chungcheongbuk-do; CN, Chungcheongnam-do; JB, Jeollabuk-do; JN, Jeollanam-do; GB, Gyeongsangbuk-do; GN, Gyeongsangnam-do; JE, Jeju-do.

b Adjusted by population of corresponding district (cases/1,000,000).

Table 2
Total number of PcP cases in non-HIV group for 2010–2021 according to sex and age
Age group Non-HIV-PcP cases

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 Average
Female 0–9 2 2 0 1 1 2 5 4 1 0 2 2 1.8
10–19 2 0 1 1 4 2 2 2 1 0 0 2 1.4
20–29 1 1 3 4 0 3 2 3 2 1 3 3 2.2
30–39 1 4 5 3 4 5 6 2 8 8 3 3 4.3
40–49 3 4 5 2 7 7 21 13 15 22 22 14 11.3
50–59 3 6 4 9 7 11 18 22 27 27 37 34 17.1
60–69 1 9 8 13 11 11 24 35 35 44 41 61 24.4
70–79 2 6 12 7 7 10 18 26 31 44 39 52 21.2
≥80 0 1 1 2 2 3 7 5 13 16 17 32 8.3

Male 0–9 0 1 1 2 3 5 4 3 5 2 0 3 2.4
10–19 2 4 3 2 2 1 2 2 2 2 3 3 2.3
20–29 3 4 4 2 5 3 5 9 16 7 5 2 5.4
30–39 8 4 14 13 11 14 19 15 12 14 17 17 13.2
40–49 9 16 17 16 15 18 18 20 22 35 24 19 19.1
50–59 8 9 18 16 13 26 29 29 28 51 45 39 25.9
60–69 9 10 11 14 10 18 28 39 58 90 106 97 40.8
70–79 5 8 12 18 11 20 40 28 52 71 92 114 39.3
≥80 1 0 2 3 3 8 10 9 22 20 34 56 14.0

Adjusted non-HIV-PcP casesa

Female 0–9 0.9 0.9 0.0 0.4 0.4 0.9 2.3 1.9 0.5 0.0 1.0 1.1 0.9
10–19 0.6 0.0 0.3 0.3 1.4 0.7 0.8 0.8 0.4 0.0 0.0 0.9 0.5
20–29 0.3 0.3 0.9 1.3 0.0 0.9 0.6 0.9 0.6 0.3 0.9 0.9 0.7
30–39 0.2 1.0 1.2 0.8 1.0 1.3 1.6 0.6 2.3 2.3 0.9 0.9 1.2
40–49 0.7 0.9 1.2 0.5 1.6 1.6 4.8 3.0 3.6 5.3 5.4 3.5 2.7
50–59 0.9 1.6 1.0 2.3 1.7 2.7 4.3 5.2 6.3 6.3 8.6 8.0 4.1
60–69 0.5 4.1 3.6 5.6 4.5 4.2 8.7 12.1 11.5 13.6 11.9 16.7 8.1
70–79 1.3 3.7 7.0 3.9 3.9 5.5 9.8 13.7 15.9 22.1 19.2 25.6 11.0
≥80 0.0 0.4 0.4 0.8 1.3 2.1 1.7 1.3 2.3 0.9 0.0 1.6 1.1

Male 0–9 0.0 0.4 0.4 0.8 1.3 2.1 1.7 1.3 2.3 0.9 0.0 1.6 1.1
10–19 0.6 1.1 0.9 0.6 0.6 0.3 0.7 0.7 0.8 0.8 1.2 1.2 0.8
20–29 0.8 1.1 1.2 0.6 1.4 0.9 1.4 2.5 4.5 2.0 1.4 0.6 1.5
30–39 1.9 0.9 3.4 3.2 2.8 3.6 4.9 4.0 3.2 3.9 4.8 4.9 3.4
40–49 2.0 3.5 3.8 3.5 3.3 4.0 4.0 4.5 5.1 8.2 5.7 4.6 4.4
50–59 2.3 2.4 4.6 4.0 3.1 6.2 6.8 6.8 6.5 11.7 10.3 8.9 6.1
60–69 4.5 5.0 5.3 6.5 4.4 7.3 10.7 14.1 20.0 29.2 32.1 27.6 13.9
70–79 4.7 7.0 9.6 13.9 8.2 14.6 28.4 18.9 33.6 44.2 55.3 67.7 25.5
≥80 3.5 0.0 6.1 8.5 7.7 18.4 21.0 17.3 38.8 32.1 50.7 78.4 23.5

a Adjusted by corresponding population of age/sex group (cases/1,000,000).

Table 3
Total number of PcP cases in HIV group for 2010–2021 according to sex and age
Age group HIV-PcP cases

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 Average
Female 0–9 0 0 0 0 0 0 0 0 0 0 0 0 0.0
10–19 0 0 0 0 0 0 0 1 0 0 0 0 0.1
20–29 1 1 2 2 2 2 3 2 1 0 0 0 1.3
30–39 3 1 4 3 2 0 1 1 3 1 2 2 1.9
40–49 1 2 2 4 2 3 3 2 3 1 2 3 2.3
50–59 5 7 5 5 2 4 5 4 4 3 4 2 4.2
60–69 2 1 1 6 6 3 4 4 7 6 6 7 4.4
≥70 0 0 0 0 0 0 1 0 0 0 0 0 0.1

Male 0–9 0 0 0 0 0 0 0 0 0 0 0 0 0.0
10–19 0 1 1 0 0 0 0 0 0 0 0 1 0.3
20–29 14 18 22 20 26 16 19 18 19 19 14 14 18.3
30–39 54 45 50 72 77 78 75 78 82 74 66 59 67.5
40–49 55 59 58 81 87 93 88 92 87 86 80 77 78.6
50–59 26 37 36 35 34 43 55 66 72 69 74 70 51.4
60–69 11 12 15 18 19 23 27 25 28 27 26 21 21.0
≥70 0 0 2 1 3 4 5 4 5 7 7 6 3.7

Adjusted HIV-PcP casesa

Female 0–9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
10–19 0.0 0.0 0.0 0.0 0.0 0.0 0.0 111.1 0.0 0.0 0.0 0.0 9.3
20–29 6.7 6.4 35.7 33.3 33.9 39.2 58.8 40.8 21.7 0.0 0.0 0.0 23.1
30–39 18.2 5.6 28.6 20.7 13.6 0.0 5.8 5.8 18.0 6.3 13.5 14.0 12.5
40–49 8.6 16.1 14.0 24.8 11.6 17.1 15.8 10.6 15.0 4.6 9.1 13.5 13.4
50–59 43.5 51.5 31.1 28.6 10.8 21.6 25.6 18.5 19.0 14.8 19.0 9.2 24.4
60–69 39.2 17.2 11.2 57.7 52.6 23.4 27.8 26.1 40.9 30.5 27.5 30.8 32.1
≥70 0.0 0.0 0.0 0.0 0.0 0.0 16.4 0.0 0.0 0.0 0.0 0.0 1.4

Male 0–9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
10–19 0.0 5.1 20.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 40.0 5.5
20–29 9.0 10.2 21.5 16.7 18.2 9.8 10.3 9.1 9.2 9.0 6.7 7.1 11.4
30–39 24.5 18.8 26.8 36.5 37.3 36.7 32.7 31.7 30.4 24.8 20.3 16.3 28.1
40–49 32.5 31.0 27.1 34.6 33.9 33.7 30.6 30.6 28.2 27.1 24.6 23.7 29.8
50–59 28.0 35.2 26.5 22.4 19.0 21.4 24.5 27.2 28.1 25.0 25.5 22.8 25.5
60–69 29.3 28.0 27.5 29.2 26.8 27.5 28.1 22.4 22.9 20.1 17.5 12.7 24.3
≥70 0.0 0.0 10.9 4.5 11.2 13.2 14.3 9.6 11.2 13.7 12.2 9.5 9.2

a Adjusted by corresponding HIV cases of age/sex group (cases/1,000).

Table 4
Regional clusters detected for PcP in the non-HIV group from 2010 to 2021
District Cases Expected Relative risk Log likelihood ratioa P-value
Seoul 1,597 591 4.59 825.231 <0.001
Jeju-do 59 37 1.59 5.431 0.02

a Clusters are shown in decreasing order of log likelihood ratio.

Table 5
Spatiotemporal Trends analysis of PcP in non-HIV group according to administrative districts (2010–2021)
Districts Cases Expected Trend inside clustera Trend outside clustera Relative risk Log likelihood ratiob P-value
Jeju-do, Jeollanam-do, Jeollabuk-do, Gyeongsangnam-do, Busan, Daejeon, Daegu, Ulsan 595 968 29.02 19.65 0.52 11.638 <0.001
Gangwon-do 59 91 25.46 21.33 0.64 0.283 1.00c

a Trend inside/outside cluster denotes % increase over the period of 2010–2021.

b Clusters are shown in decreasing order of log likelihood ratio.

c Real value: 0.9995.

Table 6
Trends of PcP in non-HIV and HIV groups according to sex and agea
Age group Trend 1 Trend 2 Trend 3



Period APCb 95% CI P-value Period APCb 95% CI P-value Period APCb 95% CI P-value

Non-HIV-PcP
Female 0–9 2010–2021 4.6 −8.1–19.1 0.46
10–19 2010–2021 1.6 −11.2–16.2 0.80
20–29 2010–2021 1.4 −7.8–11.4 0.75
30–39 2010–2021 7.2 −2.7–18.1 0.14
40–49 2010–2021 18.4 8.1–29.6 <0.01
50–59 2010–2021 21.3 16.3–26.6 <0.001
60–69 2010–2021 16.9 10.9–23.1 <0.001
70–79 2010–2021 22.5 16.2–29.1 <0.001
≥80 2010–2021 33.9 26.3–42 <0.001

Male 0–9 2010–2015 58.3 −4.2–161.6 0.07 2015–2021 −6.3 −24.5–16.2 0.50
10–19 2010–2021 2.9 −2.9–8.9 0.30
20–29 2010–2015 −0.5 −23.8–29.8 0.96 2015–2018 61.8 −35.1–303.4 0.22 2018–2021 −46.8 −71.1–−2.2 0.05c
30–39 2010–2021 7.5 2.3–12.9 0.01
40–49 2010–2021 8.0 3.3–12.9 <0.01
50–59 2010–2021 13.6 8.5–19.0 <0.001
60–69 2010–2014 1.0 −4.8–7.3 0.65 2014–2019 41.8 36.8–46.9 <0.001 2019–2021 −1.2 −7.1–5.2 0.63
70–79 2010–2021 25.8 20.9–30.9 <0.001
≥80 2010–2021 31.7 24.5–39.3 <0.001

HIV-PcP

Female 20–29 2010–2016 38.1 6.8–78.5 0.02 2016–2021 −49.1 −76.4–9.4 0.08
30–39 2010–2021 −4.7 −13.6–5.1 0.30
40–49 2010–2021 −4.2 −10.9–2.9 0.21
50–59 2010–2021 −10.8 −15.4–−6.0 <0.01
60–69 2010–2021 −3.1 −9.9–4.2 0.35

Male 20–29 2010–2012 54.5 −15.0–180.8 0.13 2012–2021 −11.6 −16.0–−6.9 <0.01
30–39 2010–2015 13.2 2.5–25.0 0.02 2015–2021 −12.6 −18.7–−6.1 <0.01
40–49 2010–2015 1.9 −3.2–7.3 0.41 2015–2021 −5.7 −9.0–−2.3 0.01
50–59 2010–2014 −13.1 −26.3–2.6 0.08 2014–2017 12.7 −25.9–71.2 0.47 2017–2021 −4.2 −14.1–6.9 0.34
60–69 2010–2018 −2.8 −5.6–0.1 0.06 2018–2021 −17.6 −26.6–−7.5 0.01
≥70 2010–2021 1.6 −5.3–9.0 0.63

a Final selected models from Joinpoint are shown.

b APC: annual percentage change.

c Real value: 0.045.

Editorial Office
Department of Molecular Parasitology, Samsung Medical Center, School of Medicine, Sungkyunkwan University,
2066 Seobu-ro, Jangan-gu, Suwon 16419, Gyeonggi-do, Korea.
Tel: +82-31-299-6251   FAX: +82-1-299-6269   E-mail: kjp.editor@gmail.com
About |  Browse Articles |  Current Issue |  For Authors and Reviewers
Copyright © 2024 by The Korean Society for Parasitology and Tropical Medicine.     Developed in M2PI