| Literature DB >> 31269906 |
Pavitra N Rao1,2, Anna Maria van Eijk1, Sandhya Choubey3, Syed Zeeshan Ali3, Aditee Dash3, Punam Barla3, Rajshri Rani Oraon3, Gautam Patel3, P Nandini3, Subrata Acharya3, Sanjib Mohanty3, Jane M Carlton4, Sanghamitra Satpathi5.
Abstract
BACKGROUND: We conducted a diagnostic surveillance study to identify Plasmodium, dengue virus, chikungunya virus, and Orientia tsutsugamushi infections among febrile patients who underwent triage for malaria in the outpatient department at Ispat General Hospital, Rourkela, Odisha, India.Entities:
Keywords: Chikungunya; Dengue; Febrile illness; India; Malaria; Scrub typhus; Surveillance
Mesh:
Substances:
Year: 2019 PMID: 31269906 PMCID: PMC6607595 DOI: 10.1186/s12879-019-4161-6
Source DB: PubMed Journal: BMC Infect Dis ISSN: 1471-2334 Impact factor: 3.090
Fig. 1Flowchart of patient testing for febrile illness. A total of 954 patients in the outpatient department at IGH, Rourkela, with reported fever up to 48 h prior to enrollment or on day of enrollment (body temperature ≥ 37.5 °C), were enrolled. All study participants were tested for Plasmodium by RDT and microscopy, and a subset of patients was tested by PCR. Patients from whom a larger volume of blood was available were tested for dengue, chikungunya and scrub typhus by RDT and ELISA
Fig. 2Clinical features of study participants. A graphical distribution of clinical features of study participants in the outpatient department at IGH, Rourkela is presented with features on the x-axis and proportion of patients on y-axis. The patients were categorized as children (15 years and below) and adults (16 years and above), with an asterisk to denote statistically significant differences between children and adults (*p = < 0.05 comparing children vs. adults)
Plasmodium infections among OPD patients as determined by RDT, microscopy and PCR, Rourkela 2016–2017
| Test | Total tested | Any species positive (%) | |||
|---|---|---|---|---|---|
| RDT | 954 | 20 (2.1) | 11 (1.2) | 0 (0) | 30 (3.1) |
| Microscopy | 954 | 16 (1.7) | 9 (0.9) | 0 (0) | 25 (2.6) |
| PCR | 852 | 39 (4.6) | 6 (0.7) | 1 (0.1) | 46 (5.4) |
Agreement of malaria tests among 852 OPD patients with all three test results available, Rourkela 2016–2017
| RDT | Microscopy | PCR | Number (%) | Species | Report of recent malaria treatment |
|---|---|---|---|---|---|
| Positive | Negative | Negative | 3 (0.4) | 2 Pf & 1 Pf + Pv | 2 Pf in previous month |
| Positive | Positive | Negative | 3 (0.4) | 1 Pf & 2 Pv | 1 Pv 4 months before |
| Positive | Negative | Positive | 2 (0.2) | 1 Pf & 1 Pv | 1 Pf in previous month |
| Positive | Positive | Positive | 20 (2.3) | 14 Pf, 5 Pv, 1 Pm* | 2 Pf and 1 Pv in previous month |
| Negative | Positive | Negative | 0 | ||
| Negative | Positive | Positive | 1 (0.1) | 1 Pf | None |
| Negative | Negative | Positive | 23 (2.7)† | All Pf | None |
| Negative | Negative | Negative | 800 (93.9) | 30 (3.8%) in previous month |
Abbreviations: Pf: P. falciparum, Pv: P. vivax, Pm: P. malariae, RDT: rapid diagnostic test, PCR: polymerase chain reaction
*P. malaria by PCR, P. vivax by RDT and microscopy
† Sub-patent malaria
Fig. 3Venn diagram of malaria test results among OPD patients, Rourkela, 2016–2017. A proportional Venn diagram representing Plasmodium positivity among 852 study participants each tested by three different assays: RDT, microscopy and PCR. Each circle represents positives by the different assays, with the numbers also shown in Table 2
Detection of dengue and chikungunya by RDT and ELISA in the 293 subjects for whom sufficient plasma was available
| Antigen | Type of test | Manufacturer (no. of patients tested) | Positive cases | % Positivity | Concordance between tests |
|---|---|---|---|---|---|
| Dengue NS1 (n = 293) | RDT | J. Mitra (n = 290) | 39 | 13.4 | NS1 RDT: J. Mitra vs. SD Bioline: 100% same results, |
| SD Bioline (n = 101) | 13 | 12.9 | |||
| ELISA | Panbio ( | 41 | 14.2 | J. Mitra RDT vs. Panbio ELISA (NS1): McNemar test, | |
| Dengue IgM (n = 293) | RDT | J. Mitra (n = 290) | 16 | 5.5 | IgM RDT: J. Mitra vs. SD Bioline: McNemar test, N = 101, exact p-value 0.625 |
| SD Bioline (n = 101) | 1 | 1 | |||
| ELISA | Panbio (n = 288) | 35 | 12.2 | J. Mitra RDT vs. Panbio ELISA (NS1): McNemar test, n = 285, exact p-value 0.688 | |
| Dengue IgG (n = 290) | RDT | J. Mitra ( | 8 | 2.8 | IgG RDT: J. Mitra vs. SD Bioline: 100% same results, |
| SD Bioline (n = 101) | 2 | 2 | |||
| Dengue NS1 or Dengue IgG or Dengue IgM | RDT or ELISA | J. Mitra or SD Bioline or Panbio (n = 293) | 74 | 25.3 | Not applicable |
| chikungunya IgM ( | RDT | J. Mitra (n = 288) | 8 | 2.8 | IgM RDT: J. Mitra vs. SD Bioline: McNemar test, |
| SD Bioline ( | 0 | 0 | |||
| ELISA | Panbio ( | 15 | 5.2 | J. Mitra RDT vs. Panbio IgM ELISA: McNemar test, | |
| RDT or ELISA | J. Mitra or SD Bioline or Panbio ( | 17 | 5.8 | Not applicable |
Fig. 4Venn diagram of select dengue test results among OPD patients, Rourkela, 2016–2017. A proportional Venn diagram representing dengue positivity among 288 study participants tested by three different assays: J. Mitra NS1 RDT, NS1 ELISA, and DENV-specific IgM ELISA. The numbers in each compartment of the Venn diagram are depicted on the graph
Characteristics and O.D. values of study participants positive for scrub typhus by ELISA
| Subject | O.D. value | Age | Sex | Month of sample collection |
|---|---|---|---|---|
| IS0585 | 2.531 | 48 | Male | August |
| IS0697 | 1.113 | 37 | Female | September |
| IS0527 | 1.049 | 35 | Female | August |
| IS0642 | 0.716 | 26 | Female | August |
| IS0595 | 0.702 | 62 | Male | August |
| IS0743 | 0.685 | 16 | Male | September |
| IS0477 | 0.678 | 23 | Male | July |
| IS0593 | 0.669 | 45 | Female | August |
| IS0525 | 0.599 | 32 | Male | August |
| IS0783 | 0.598 | 40 | Male | September |
*All samples tested for scrub typhus were collected between July 2016 and January 2017
Characteristics of 17 outpatients with multiple infections among 290 patients with at least three tests, Rourkela, 2016–2017
| Tests with positive results | ||||||||
|---|---|---|---|---|---|---|---|---|
| Patient | Positive for | CHIKV | DENV | Pf | Scrub typhus | Age | Gender | Month |
| IS0596 | CHIKV, DENV, Pf | J. Mitra IgM RDT | J. Mitra IgM RDT | RDT, BS & PCR | NA | 35 | Male | August |
| IS0525 | Scrub typhus, Pf | NA | NA | RDT, BS & PCR | IgM ELISA | 32 | Male | August |
| IS0642 | Scrub typhus, DENV | NA | IgM ELISA & NS1 ELISA | NA | IgM ELISA | 26 | Female | August |
| IS0585 | Scrub typhus, DENV | NA | IgM ELISA | NA | IgM ELISA | 48 | Male | August |
| IS0783 | Scrub typhus, DENV | NA | IgM ELISA | NA | IgM ELISA | 40 | Male | September |
| IS0697 | Scrub typhus, DENV | NA | NS1 ELISA | NA | IgM ELISA | 37 | Female | September |
| IS0595 | Scrub typhus, DENV | NA | J. Mitra IgM RDT | NA | IgM ELISA | 62 | Male | August |
| IS0743 | Scrub typhus, DENV | NA | J. Mitra IgM RDT | NA | IgM ELISA | 16 | Male | September |
| IS0477 | Scrub typhus, CHIKV | IgM ELISA | NA | NA | IgM ELISA | 23 | Male | July |
| IS0742 | DENV, Pf | NA | NS1 ELISA | PCR | NA | 40 | Female | September |
| IS0731 | CHIKV, Pf | IgM ELISA & J. Mitra IgM RDT | NA | RDT, BS & PCR | NA | 42 | Male | September |
| IS0849 | CHIKV, Pf | IgM ELISA & J. Mitra IgM RDT | NA | RDT, BS & PCR | NA | 16 | Male | October |
| IS0695 | CHIKV, Pf | IgM ELISA & J. Mitra IgM RDT | NA | PCR | NA | 69 | Male | September |
| IS0674 | CHIKV, Pf | IgM ELISA & J. Mitra IgM RDT | NA | RDT | NA | 14 | Male | September |
| IS0848 | CHIKV, DENV | IgM ELISA | IgM ELISA | NA | NA | 14 | Female | October |
| IS0815 | CHIKV, DENV | IgM ELISA | NS1 ELISA, J. Mitra IgM RDT, J. Mitra IgG RDT | NA | NA | 24 | Male | October |
| IS0586 | CHIKV, DENV | J. Mitra IgM RDT | NS1 ELISA, IgM ELISA, J. Mitra NS1 RDT | NA | NA | 37 | Male | August |
Pf: P. falciparum, CHIKV: chikungunya virus, DENV: Dengue virus, NA: Not applicable, RDT: rapid diagnostic test, BS: blood smear (microscopy), PCR: polymerase chain reaction
Summary of results from six febrile illness studies from India, 2007–2017
| Study | Location and year | Population and sample size | Select tests and results | Results (n, %) |
|---|---|---|---|---|
| Chrispal 2010 | Christian medical college, Vellore; 2007 | ≥16 years, febrile for 5–21 days, in-patients | 1) Thin blood smear for malaria 2) Dengue IgM-IgG ELISA 3) Scrub typhus IgM ELISA 4) Blood culture or Typhidot for Salmonella 5) Leptospirosis IgM ELISA 6) Spotted fever IgM ELISA 7) Hantavirus IgM and IgG | Malaria (68, 17.1%) Dengue (28, 7.0%) Scrub typhus (189, 47.5%) Enteric fever (32, 8.0%) Leptospirosis (12, 3.0%) Spotted fever (7, 1.8%) Hantavirus (1, 0.3%) |
| Mittal 2015 | Himalayan Institute of Medical Sciences, Dehradun, Dec 2012- Nov 2013 | > 18 years, febrile for 5–14 days, in-patients | 1) Malaria microscopy, RDT 2) Scrub typhus IgM ELISA 3) Dengue NS1/ IgM RDT 4) Leptospira IgM RDT 5) Widal Ag kit for Salmonella 6) Anti HEV IgM EIA 7) Anti HAV IgM EIA | Malaria (175, 6.8%); Scrub typhus (367, 14.4%); Dengue (956, 37.5%); Leptospirosis (0.14%); Enteric fever (424, 16.5%); Hepatitis A (1.9%); Hepatitis E (1.4%); Undetermined 11%. Mixed infections (48, 1.9%) |
| Abhilash 2016 | Christian medical college, Vellore; Oct 2012- Sep 2013 | ≥16 years, febrile for 3–14 days, Both in-patients and out-patients | 1) Thin blood smear for malaria 2) Dengue IgM-IgG ELISA 3) Scrub typhus IgM ELISA 4) Blood culture for Salmonella, Widal 5) Leptospirosis IgM ELISA | Malaria (131, 10.4%) Dengue (386, 30.6%) Scrub typhus (452, 35.9%) Enteric fever (47, 3.7%) Leptospirosis (8, 0.6%) Undetermined (220, 17.4%) |
| Morch 2017 | 7 hospitals in India, April 2011- Nov 2012 | ≥5 years, in-patients | 1) Malaria PCR, RDT, microscopy 2) Dengue RDT, IgM ELISA 3) chikungunya IgM ELISA 4) Leptospirosis IgM ELISA 5) Scrub typhus IgM ELISA 6) Blood culture for bacterial infections | Malaria (268, 17%) Dengue (244, 16%) chikungunya (98, 6%) Leptospirosis (116, 7%) Scrub typhus (159, 10%) Bacteremia (124, 8%) |
| Robinson 2018 | BJ Medical College, Pune; 2013–2015 | > 6 months, fever or complaint of fever, in-patients | 1) Malaria RDT, microscopy 2) Dengue NS1 ELISA, IgM 3) chikungunya IgM RDT 4) Influenza RDT 5) Leptospirosis IgM | Malaria (102, 6%) Dengue (252, 15%) chikungunya (35, 2%) Influenza (13, 0.8%) Leptospirosis (18, 1%) Mixed mosquito borne infections (23, 1%) Undetermined (965, 56%) |
| MCVR report 2017 | 27 hospital-based sentinel sites, June 2014–July 2017 | in-patients | 1) PCR for Influenza 2) Dengue IgM, IgG ELISA, PCR 3) Scrub typhus IgM ELISA and PCR 4) Leptospirosis IgM ELISA, PCR, MAT 5) Malaria RDT, PCR 6) chikungunya IgM ELISA, PCR | Influenza (4118, 15%) Dengue (1898, 7%) Scrub typhus (1177, 4%) Leptospirosis (1107, 4%) Malaria (953, 3%) chikungunya (371, 1%) |