| Literature DB >> 35183188 |
Annette Onken1,2,3, Christel Gill Haanshuus4, Mohammed Khamis Miraji5, Msafiri Marijani6, Kibwana Omar Kibwana6, Khamis Ali Abeid7, Kristine Mørch8,4, Marianne Reimers9,10, Nina Langeland8,4, Fredrik Müller11,12, Pål A Jenum13,12, Bjørn Blomberg8,4.
Abstract
BACKGROUND: Control efforts in Zanzibar reduced the burden of malaria substantially from 2000 to 2015, but re-emergence of falciparum malaria has been observed lately. This study evaluated the prevalence of malaria and performance of routine diagnostic tests among hospitalized fever patients in a 1.5 years period in 2015 and 2016.Entities:
Keywords: Eastern Africa; Fever; Malaria; Microscopy; Point-of-care diagnostic tests; Polymerase chain reaction; Prevalence; Surveillance; Tanzania; Zanzibar
Mesh:
Year: 2022 PMID: 35183188 PMCID: PMC8858509 DOI: 10.1186/s12936-022-04067-z
Source DB: PubMed Journal: Malar J ISSN: 1475-2875 Impact factor: 2.979
Fig. 3Malaria parasitaemia by age group (years) and result of microscopy and malaria rapid diagnostic test (RDT). Quantitation of parasitaemia by real-time PCR by diagnostic modalities expressed as log-transformed values of copies per µL blood. Unit of measurement for parasitaemia by PCR is described in the section PCR methods. Dots represent individual observations. Number tested in brackets. * Kruskal Wallis test † Wilcoxon rank sum test
Fig. 2An overview and results from the analyses performed by PCR, RDT and routine microscopy. The numbers in the circles refer to malaria positive results performed by each method. The numbers of malaria negatives are given in the bottom of the squares. Except for the malaria prevalence, all numbers are given for the performance of each method independently of false positives/negatives by the gold standard method PCR
Performance of RDT and microscopy compared to PCR among patients hospitalized with fever in Zanzibar (total n = 820)
| RDT (n = 631) | Microscopy (n = 290) | |
|---|---|---|
| Percentage (n/total) | Percentage (n/total) | |
| Sensitivity | 64% (36/56) | 50% (18/36) |
| Specificity | 98% (561/575) | 99% (251/254) |
| Positive predictive value | 72% (36/50) | 86% (18/21) |
| Negative predictive value | 97% (561/581) | 93% (251/269) |
Numbers given for patients investigated with PCR and each test. Discrepancies are due to missing values
RDT, rapid diagnostic test; PCR, polymerase chain reaction
Fig. 1Patients included and analyses performed
Fig. 4Malaria cases by age groups. Number of malaria patients (blue bars) among febrile patients (grey bars) and percentage positive (line) in different age groups
Comparison of malaria prevalence and parasitaemia by age groups
| Age group | Positive | OR (CI)p* | Parasitaemia | p† |
|---|---|---|---|---|
| Under 5 | 5% (14/260) | ref. | 22 (4-236) | ref. |
| 5-15 years | 15% (20/131) | 1.10 (1.04-1.17) | 65 (25-488) | 0.30 |
| 16-30 years | 13% (15/119) | 1.07 (1.01-1.14) | 111 (6-427) | 0.41 |
| Over 30 | 6% (14/217) | 1.01 (0.96-1.06) 0.678 | 28 (0.05-170) | 0.65 |
* Logistic regression (glm in R)
†Kruskal–Wallis test and pairwise Wilcoxon rank sum test for multiple comparisons
Fig. 5Monthly number of malaria cases and monthly rainfall from February 2015 to October 2016. Rainfall data for Dar es Salaam from the Tanzanian Meteorological Agency (TMA) [35, 36]. Study start March 17, 2015, study end October 4, 2016