Global prevalence of haemosporidian parasites in wild birds: Systematic review and meta-analysis

Abstract

Haemosporidians (Plasmodium, Haemoproteus, and Leucocytozoon) are blood parasites that infect birds and other vertebrates worldwide. Infections can cause disease that reduces survival and reproductive success, and may even lead to mortality. They are primarily assessed through prevalence, a population parameter that varies among species, regions, and seasons due to environmental and ecological factors. Although meta-analyses on this parameter exist, none globally synthesize data across the three haemosporidian genera and current detection methods (PCR and microscopy). The objective of this systematic review was to determine the overall prevalence of haemosporidian parasites in wild birds distributed across different zoogeographic regions. The review was conducted following the methodology proposed by the Joanna Briggs Institute (JBI) for scoping reviews and was reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) to estimate pooled prevalence and assess variation according to diagnostic method, continent, parasite genus, and bird family. The global pooled prevalence was 12.3%, with estimates of 12.1% by PCR and 13.1% by microscopy. Regardless of the diagnostic method, the continents with the highest prevalence were Africa (P_MIC = 22.3%; P_PCR = 13.5%) and Europe (P_MIC = 28.6%; P_PCR = 12.6%). The high heterogeneity among studies suggests that multiple biological, environmental, and methodological factors contribute to global variation in infection patterns. This study provides the first global reference of haemosporidian parasite prevalence in wild birds and highlights the need for standardized reporting of environmental and methodological variables to better understand the drivers of avian malaria dynamics.

Keywords

Avian haemosporidians prevalence wild birds disease meta-analysis

Introduction

Haemosporidians are intracellular protist parasites belonging to the phylum Apicomplexa [1]. They infect a wide range of vertebrate hosts, including birds, mammals, and reptiles^1,2. Their heteroxenous life cycle requires both a vertebrate host and a hematophagous dipteran vector, facilitating their broad global distribution^1,3. These infections are of considerable ecological and epidemiological relevance, as they can cause anemia, reduced survival and reproductive success, and even high mortality in host populations^1,4–7.

Prevalence, defined as the percentage of infected individuals relative to the total population at a given time⁸, is an important metric for assessing the impact and dynamics of these parasites.⁹ It can be assessed at different biological levels, including within a single host species or across multiple species within a community¹⁰. Its magnitude can vary widely (0–100%) among species, regions, and seasons, depending on abiotic factors such as altitude and climatic conditions that favor transmission, as well as biotic factors such as vector availability and host exposure^11–13. Additionally, migratory birds often exhibit higher prevalence and greater diversity of parasite lineages, highlighting the role of host movement in dispersing these parasites¹⁴.

Clark et al. (2014) highlighted that avian haemosporidians exhibit diversity patterns similar to those of their avian hosts, a key finding for understanding lineage diversity and host–parasite interactions in Plasmodium and Haemoproteus. Although this synthesis focused on parasite diversity, which is essential for elucidating evolutionary and phylogenetic patterns, it does not quantify infection prevalence in wild birds, a population parameter⁸ required to understand the distribution of each parasite genus, identify the factors driving their transmission, and evaluate their implications for the conservation and health of wild bird populations^15,16.

Quantitative syntheses of haemosporidian prevalence are comparatively limited. To date, only two systematic reviews with meta-analysis have been published. The first focused exclusively on Plasmodium infections in wild birds¹⁷. More recently, Swangneat et al.¹⁸ expanded the analysis to include the three main haemosporidian genera; however, they restricted inclusion to PCR-based studies conducted in Southeast Asia, most of which involved domestic or captive birds. Consequently, pooled prevalence estimates integrating Plasmodium, Haemoproteus, and Leucocytozoon across wild bird populations at a global scale remain lacking, particularly those that explicitly account for differences between diagnostic approaches (microscopy and PCR).

Synthesizing the prevalence of haemosporidian parasite infections substantially contributes to the ecological and epidemiological understanding of avian malaria. Prevalence not only represents the proportion of infected individuals, but also serves as an indirect indicator of transmission intensity and host–parasite dynamics across different environmental and biogeographic contexts¹⁹. Integrating estimates at a global scale allows the identification of spatial gradients, the assessment of potential environmental and methodological effects, and the detection of heterogeneity patterns that are not evident in individual studies. Such syntheses also provide comparable baseline values across regions and taxa, facilitate evaluation of impacts on wild population health, and help identify geographic and taxonomic gaps that can guide future research and surveillance strategies.

Therefore, the aim of this study was to conduct a systematic review and meta-analysis of haemosporidian parasite prevalence in wild birds, assessing variation by diagnostic method, continent, parasite genus, and bird family, while providing a population level perspective.

Materials and methods

Inclusion criteria

Participants

The review considered studies conducted with blood samples from wild birds collected in the field or stored in blood banks. In studies that involved both wild and captive or domestic birds, they were considered only if the authors reported data for each group separately.

Condition

This review included studies on the prevalence of haemosporidian parasites, which are blood parasites that require a vector (dipteran) and a host (bird) to complete their life cycle, thereby affecting the health of infected individuals²⁰.

Context

This review did not apply any geographical restrictions in the selection of studies.

Types of studies

The review included observational cross-sectional studies that assessed natural infections in wild birds that used molecular or microscopic techniques for the detection and identification of haemosporidian parasites. Experimental infection studies involving artificial inoculation under laboratory conditions were excluded. We also considered both studies published in peer-reviewed scientific journals and grey literature obtained through systematic searches in specialized databases or repositories.

The systematic review was conducted in accordance with the methodology proposed by the Joanna Briggs Institute (JBI)²¹ and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines²².

Search strategy

The objective of the search strategy was to identify both published studies and grey literature in three steps. (1) A search was conducted in PUBMED, followed by an analysis of the keywords contained in the title and abstract, as well as the index terms used to describe the article. (2) A second search was performed using all identified keywords and index terms across all included databases. (3) We examined the reference lists of all articles included in the review to locate additional studies.

The resources consulted included PubMed, ScienceDirect, Web of Science, Scopus, ProQuest (ProQuest Central, Academic Complete, Academic Video Online, and ProQuest Dissertations & Theses), LILACS, and Google Scholar. The grey literature search included the repository La Referencia. The initial keywords used were: birds, wildlife, blood sample, and haemosporidian parasites. We considered only studies published in English, Spanish, and Portuguese for inclusion in this review. We did not apply any time restrictions to the searches. We detail the search equations used for each consulted resource in S2 Table. Below is the equation used in PubMed:

1. birds[MeSH Terms]

2. Aves[Title/Abstract] OR birds[Title/Abstract] OR avian[Title/Abstract].

3. #1 OR #2.

4. Animals, Wild[MeSH Terms].

5. (Wild[Title/Abstract] OR “Non-domesticated”[Title/Abstract] OR nondomesticated[Title/Abstract] OR undomesticated[Title/Abstract] OR feral[Title/Abstract] OR stray[Title/Abstract].

6. #4 OR #5.

7. Prevalence[Title/Abstract].

8. Haemosporida[MeSH Terms] OR malaria, avian[MeSH Terms].

9. Haemosporidia[Title/Abstract] OR Apicomplexa[Title/Abstract] OR Plasmodium[Title/Abstract] OR Leucocytozoon*[Title/Abstract] OR Haemoproteus[Title/Abstract] OR “Avian haematozoa”[Title/Abstract].

10. #8 OR #9.

11. #3 AND #6 AND #7 AND #10.

All searches were conducted independently by two reviewers to ensure the reproducibility and methodological rigor of the process.

Study selection

The search results were managed in Mendeley (version 2.77.0) in order to remove duplicate records. Subsequently, we carried out document screening using the Rayyan program²³. Two reviewers (TBT and LJR) independently examined the titles and abstracts of the retrieved studies, based on the previously defined inclusion criteria, to determine their eligibility for full-text review. In cases where discrepancies arose between reviewers during the selection process, the third reviewer (FRG) resolved them. We present the results of the searches and the study selection process in a flow diagram, in accordance with the PRISMA guidelines (Figure 1).

Figure 1.

Flow diagram of the study design process.

Methodological quality assessment

Two reviewers independently assessed the methodological quality of the studies that met the inclusion criteria. For this evaluation, the checklist for prevalence studies developed by the Joanna Briggs Institute (JBI) was adapted²². The questions considered in the evaluation were: Were the study participants sampled appropriately? Was the sample size adequate? Were the study subjects and setting described in detail? Were valid methods used to identify the condition? Was the condition measured in a standardized and reliable way for all participants? Was an appropriate statistical analysis conducted?

To ensure the methodological quality of the studies included in the review, a minimum criterion was established requiring each study to meet at least four of the six items adapted from the Joanna Briggs Institute (JBI) checklist for prevalence studies. This decision was based on the need to minimize the risk of bias and ensure that the estimates obtained came from studies with an acceptable level of scientific rigor. The authors assumed that including only studies that met at least four of the six evaluated criteria would allow the analyzed sample to be composed of research that, although potentially subject to certain limitations, met basic standards of validity in fundamental aspects such as sampling, sample size, validity of diagnostic methods, and statistical analysis.

Data extraction

Descriptive and relevant data from the studies included in the review were extracted using a standardized table created in an Excel spreadsheet S3 Data. One reviewer performed the extraction and subsequently verified it by a second reviewer to ensure the accuracy and consistency of the collected information.

Data analysis and presentation

The data extracted from the included studies were used to perform the meta-analysis using R software (v. 2025.05.1+513). The extracted variables included: author and year of publication, total sample size (n), number of infections of positive individuals, continent, diagnostic methodology (PCR or microscopy), host family, parasite species, and geographic and environmental variables (altitude, latitude, longitude, and temperature). When studies included multiple host species within a community, prevalence data were extracted and analyzed separately for each species, treating each as an independent record. These variables were used to calculate prevalence estimates and to explore potential sources of heterogeneity through subgroup analyses and meta-regression models.

For the meta-analysis, studies with extreme prevalence values (1% or 100%) and those with fewer than 50 individuals were excluded. This exclusion is based on the fact that small samples tend to generate unstable estimates with high variability, thereby increasing the risk of random error²⁴. In the context of prevalence studies, small sample sizes may yield results that are not representative of the target population, thereby reducing the precision of the estimates. Studies with very small sample sizes often have low statistical power, which makes it difficult to detect true patterns and compare them with those of other studies included in the meta-analysis²⁵. For these reasons, a minimum threshold of 50 individuals was established to improve the quality and consistency of the analyzed data. Heterogeneity among studies was statistically assessed using the I² test, where estimates above 75% were considered indicative of significant heterogeneity. Likewise, the τ² statistic was estimated to indicate the actual variance among study effects²⁶. A random-effects model was employed to synthesize prevalence values using the R packages meta (version 8.2-1)²⁷ and metafor (version 4.8-0)²⁸. Subgroup analyses were conducted to assess whether family, identification method, and biogeographic region influenced infection prevalence, using Cochran’s Q test to evaluate these differences²⁹ in the meta package.

Meta-regression analysis were conducted to evaluate the effect of publication year, temperature, altitude (meters above sea level), and latitude on prevalence estimates derived from PCR and microscopy. Environmental and spatial data were extracted directly from each article when available. In cases where it was not possible to explicitly retrieve geographic coordinates of latitude and longitude and the sampling location was identified, QGIS (version 3.34.12)³⁰ was used to obtain altitude (meters above sea level) and environmental temperature using the SRTM 30s Digital Elevation Model³¹ and WorldClim 2.1³² (BIO1, 30-second arc resolution), respectively. The resulting dataset was exported as a CSV file and incorporated into subsequent meta-regression analysis in R. Meta-regression models were fitted using the metafor package with restricted maximum likelihood estimation (REML). A leave-one-out sensitivity analysis²⁸ was also applied for each subgroup meta-analysis to assess the influence of individual studies on prevalence results using the metafor package.

Publication bias was not evaluated because conventional methods, such as funnel plots, may generate false asymmetry in proportion studies, particularly when small samples, extreme proportions, or zero events are present³³. Moreover, it has been pointed out that applying these tests—originally developed for clinical trials—to prevalence studies is inappropriate and may lead to misleading conclusions³⁴. Therefore, given the limited use of these tools in this type of research, all articles were included without individual evaluation of publication bias. The results are presented in tables and figures, accompanied by a narrative synthesis, to provide an adequate response to the review question.

Results

The search strategy identified a total of 1915 studies. After removing 482 duplicates, 1433 studies remained. Following the application of inclusion criteria based on title and abstract, 865 studies were excluded, leaving 568 for full-text review. However, the full text of 27 of these could not be retrieved. After assessment, 351 studies met the inclusion criteria of this review and were subjected to methodological quality evaluation (Figure 1).

Methodological quality assessment

A total of 206 studies achieved acceptable methodological quality; of these, 91 met all six established criteria, 109 met five criteria, and six met four criteria (S1 Data).

Characteristics of the included studies

The included studies were published between 1982 and 2024, in Spanish, English, and Portuguese, and reported the identification of haemosporidians using PCR, microscopy, or both methods. In total, the studies analyzed encompassed 135 bird families. Altogether, the included studies documented 36,401 specimens infected with haemosporidians, representing the total number of positive individuals reported in the selected publications.

The investigations were based on samples collected in 65 countries across all inhabited continents. The countries with the highest number of studies were: United States (38 studies), Brazil (22 studies), Spain (11), Germany (9), Mexico (9), Colombia (7), Ecuador (8), Bulgaria (7), New Zealand (6), Chile (4), and China (5) (Figure 2). At the continental level, the distribution of study samples was as follows: America (89 studies), Europe (65), Asia (23), Africa (26), and Oceania (13).

Figure 2.

Global prevalence of haemosporidian parasites in wild birds across different zoogeographic regions.

Pooled prevalence by diagnostic method

Overall

A total of 181 studies were included, showing high heterogeneity (I² = 97.8%, τ² = 3.00). Across these studies, 333,653 individuals were assessed, of which 32,290 were infected with haemosporidians, yielding a crude prevalence of P= 9.7%. The random-effects meta-analysis of proportions estimated the pooled prevalence at P= 12.3% (95% CI: 0.1096–0.1377).

PCR

Based on 137 studies using PCR, the estimated pooled prevalence was P= 12.1% (95% CI: 0.1063–0.1380). These studies also showed high heterogeneity (I² = 97.7%, τ² = 2.93).

PCR – pooled prevalence by continent

The estimated prevalence by continent was P= 13.5% in Africa (I² = 97.4%), P = 12.6% in Europe (I² = 98.1%), P= 12.6% in the Americas (I² = 97.1%), P= 10.9% in Asia (I² = 95.4%), and P= 5.0% in Oceania (I² = 98.3%). Despite these differences in point estimates, no statistically significant differences were found among continents (Q = 6.16; df = 4; p = 0.1878) (Table 1).

Table 1.

Meta-analysis by subgroups based on continent and parasite species according to the diagnostic method in the included studies.

Metodology	Variables	# estudies	# observations	%Prevalence	I²	T²	Interval	P
Overall	All	181	716	12.3	97.80%	3	2,7841; 3,4841	<0.001
Overall	All	137	538	12.1	97.70%	2.9	2,6637; 3,4503	<0.001
Overall - PCR	All	137	538	12.1	97.70%	2.9	2,6637; 3,4503	<0.001
Continent - PCR	Africa	21	140	13.5	97.40%	1.95	0,1091 - 0,1648	0.187
	Europe	44	159	12.6	98.10%	3639	0,0959 - 0,1629	0.187
	America	52	168	12.6	97.10%	3136	0,0989 - 0,1597	0.187
	Oceanía	10	24	5	98.30%	4504	0,0217 - 0,1113	0.187
	Asia	12	47	10.9	95.40%	1597	0,0771 - 0,1526	0.187
Overall haemosporidio - PCR	Haemoproteus	105	207	14.2	97.30%	2.5	0,1168 - 0,1708	0.14
	Leucocytozoon	59	121	10	98.40%	4081	0,0715 - 0,1385	0.14
	Plasmodium	111	210	11.6	97.30%	2702	0,0944 - 0,1414	0.14
Family of birds - PCR	Accipitridae	7	13	15.6	97.50%	2043	0,0766; 0,2914	<0.001
	Acanthizidae	1	2	4.1	80.80%	1276	0,0075; 0,1935	<0.001
	Acrocephalidae	11	28	7.6	96.90%	3077	0,0402; 0,1402	<0.001
	Alaudidae	1	2	0.7	0	0	0,0017; 0,0270	<0.001
	Anatidae	5	13	10.2	98.20%	2065	0,0490; 0,2015	<0.001
	Bernieridae	2	4	12.2	81.10%	0.77	0,0499; 0,2681	<0.001
	Cardinalidae	4	8	21.8	93.40%	1139	0,1146; 0,3752	<0.001
	Cettiidae	2	2	57	0	0	0,5287; 0,6110	<0.001
	Charadriidae	1	2	0.2	0	0	0,0008; 0,0042	<0.001
	Cinclidae	1	3	11.7	95.90%	5697	0,0082; 0,6813	<0.001
	Columbidae	4	8	20.8	97.80%	1.66	0,0962; 0,3940	<0.001
	Coerebidae	3	2	15.2	83.70%	0.464	0,0599; 0,3335	<0.001
	Corvidae	3	7	20.6	94.90%	1669	0,0880; 0,4114	<0.001
	Cotingidae	2	2	1.1	98.60%	21.03	0,0000; 0,8725	<0.001
	Emberizidae	10	19	18.6	97.80%	3505	0,0889; 0,3493	<0.001
	Estrildidae	5	9	2.9	96.10%	5466	0,0061; 0,1277	<0.001
	Fringillidae	11	21	16.2	94.70%	1656	0,0983; 0,2539	<0.001
	Furnariidae	3	5	6	96.80%	2367	0,0157; 0,2021	<0.001
	Hirundinidae	5	10	19.8	98.60%	2734	0,0792; 0,4133	<0.001
	Icteridae	3	4	40.5	89.80%	5641	0,0591; 0,8807	<0.001
	Laniidae	2	4	48.8	89.20%	0.396	0,3318; 0,6466	<0.001
	Laridae	3	4	26.5	98.60%	10.86	0,0137; 0,9031	<0.001
	Meliphagidae	2	3	12.4	98.00%	4696	0,0116; 0,6311	<0.001
	Meropidae	1	2	61.3	0	0	0,5829; 0,6420	<0.001
	Mimidae	1	3	18.2	93.40%	1398	0,0521; 0,4745	<0.001
	Muscicapidae	14	34	6.3	96.50%	1427	0,0423; 0,0934	<0.001
	Nectariniidae	9	20	22.5	93.80%	1131	0,1522; 0,3197	<0.001
	Pachycephalidae	1	2	11.2	95.90%	3.43	0,0091; 0,6339	<0.001
	Panuridae	2	3	6.1	27.60%	0.189	0,0275; 0,1310	<0.001
	Paridae	15	36	17.2	98.60%	4.02	0,0967; 0,2874	<0.001
	Parulidae	9	14	12.8	95.00%	2.19	0,0622; 0,2454	<0.001
	Passerellidae	9	16	19.2	97.60%	1311	0,1180; 0,2973	<0.001
	Passeridae	14	30	15.3	97.00%	2434	0,0919; 0,2441	<0.001
	Pellorneidae	1	2	13.1	95.60%	1987	0,0201; 0,5272	<0.001
	Petroicidae	3	4	8.3	97.50%	4537	0,0105; 0,4365	<0.001
	Phalacrocoracidae	1	2	2.6	0	0	0,0116; 0,0562	<0.001
	Phasianidae	3	6	26.6	98.30%	1432	0,1211; 0,4885	<0.001
	Phylloscopidae	2	3	6.7	98.30%	4.91	0,0056; 0,4769	<0.001
	Ploceidae	8	24	10.8	98.60%	2417	0,0608; 0,1862	<0.001
	Promeropidae	1	2	1.8	92.80%	6648	0,0004; 0,4182	<0.001
	Prunellidae	1	2	36.2	93.70%	0.651	0,1518; 0,6434	<0.001
	Pycnonotidae	10	23	11.5	94.40%	1757	0,0689; 0,1872	<0.001
	Rallidae	1	3	5.5	34.90%	0.086	0,0316; 0,0936	<0.001
	Rynchopidae	1	2	20.2	0	0	0,1518; 0,2637	<0.001
	Scolopacidae	3	6	2	97.70%	3.04	0,0049; 0,0783	<0.001
	Strigidae	1	2	72.9	0	0	0,6797; 0,7740	<0.001
	Sturnidae	3	4	12	96.70%	1945	0,0322; 0,3592	<0.001
	Sylviidae	7	16	8.3	97.40%	2587	0,0386; 0,1689	<0.001
	Thamnophilidae	3	3	18.5	92.20%	0.928	0,0663; 0,4201	<0.001
	Thraupidae	12	20	13.4	97.90%	2977	0,0666; 0,2503	<0.001
	Trochilidae	5	6	10.6	98.20%	8.8	0,0107; 0,5630	<0.001
	Turdidae	13	28	9.7	95.80%	2778	0,0536; 0,1700	<0.001
	Tyrannidae	9	12	6	93.50%	3257	0,0212; 0,1555	<0.001
	Vangidae	1	2	12.7	12.00%	0.022	0,0762; 0,2048	<0.001
	Vireonidae	1	2	10.9	86.10%	1914	0,0153; 0,4885	<0.001
	Zosteropidae	5	11	28	98.50%	4817	0,0953; 0,5904	<0.001
Overall -microscopy	All	51	178	13.1	97.9 %	3.2	2,7271 - 4,2838	<0.001
Continent - microscopy	África	4	23	22.3	95.5 %	1207	1,1524; 0,3136	0,0006
	Europa	12	28	28.5	96.9 %	2586	0.178 – 0.422	0,0006
	America	28	105	8.8	98.2 %	3725	0.624– 0.123	0,0006
	Asia	6	21	15.7	96.0 %	2.1	0.898– 0.260	0,0006
Overall haemosporidia - microscopy	Haemoproteus	45	75	23.2	97.30%	1473	0,1855 - 0,2855	<0,0001
	Leucocytozoon	18	41	6.1	98.90%	7.26	0,0277 - 0,1315	<0,0001
	Plasmodium	30	62	9.8	96.20%	2066	0,0698 - 0,1336	<0,0001
Family of birds – Microscopy	Acrocephalidae	4	6	11.3	95.60%	2187	0,0357; 0,3067	<0,0001
	Anatidae	2	5	10	98.90%	1143	0,0413; 0,2223	<0,0001
	Ardeidae	2	2	3.5	63.90%	0.3	0,0139; 0,0858	<0,0001
	Cardinalidae	1	2	10.7	38.80%	0.026	0,0770; 0,1465	<0,0001
	Columbidae	7	9	40.3	97.60%	2336	0,1950; 0,6531	<0,0001
	Corvidae	1	2	30	92.10%	0.361	0,1524; 0,5052	<0,0001
	Cotingidae	3	3	2	97.70%	5842	0,0013; 0,2518	<0,0001
	Emberizidae	6	13	9.9	98.60%	2719	0,0419; 0,2151	<0,0001
	Fringillidae	4	8	31.7	98.50%	3894	0,1044; 0,6481	<0,0001
	Furnariidae	2	2	0.6	95.80%	13.32	0,0000; 0,5272	<0,0001
	Hirundinidae	2	2	47	99.70%	10.74	0,0093; 0,9882	<0,0001
	Icteridae	4	10	9.3	97.70%	2425	0,0368; 0,2174	<0,0001
	Mimidae	2	4	7.3	96.10%	3185	0,0125; 0,3275	<0,0001
	Motacillidae	1	2	20.3	98.90%	3591	0,0178; 0,7813	<0,0001
	Muscicapidae	5	8	33.8	93.50%	1086	0,1956; 0,5182	<0,0001
	Nectariniidae	3	9	31.8	92.90%	0.915	0,1964; 0,4710	<0,0001
	Paridae	4	7	21.2	83.60%	0.572	0,1280; 0,3298	<0,0001
	Parulidae	6	9	7.1	95.70%	3823	0,0206; 0,2195	<0,0001
	Passeridae	4	7	9.5	91.70%	0.974	0,0454; 0,1870	<0,0001
	Phasianidae	2	2	33.8	96.40%	1325	0,0913; 0,7215	<0,0001
	Phylloscopidae	1	2	3.6	0	0	0,0173; 0,0739	<0,0001
	Ploceidae	2	4	11.4	95.00%	0.862	0,0482; 0,2464	<0,0001
	Prunellidae	1	2	23.2	92.50%	0.723	0,0817; 0,5074	<0,0001
	Pycnonotidae	2	3	25.4	98.50%	3275	0,0415; 0,7286	<0,0001
	Strigidae	1	3	14.8	95.70%	1916	0,0336; 0,4631	<0,0001
	Sylviidae	2	7	15.6	96.90%	1.77	0,0631; 0,3360	<0,0001
	Thraupidae	6	10	8.7	99.10%	4243	0,0257; 0,2578	<0,0001
	Trochilidae	4	4	15.4	98.70%	18.7	0,0026; 0,9281	<0,0001
	Troglodytidae	2	2	0.4	91.50%	8141	0,0001; 0,1863	<0,0001
	Turdidae	3	7	5.9	97.10%	1514	0,0240; 0,1387	<0,0001
	Tyrannidae	5	8	5.5	93%	3404	0,0154; 0,1786	<0,0001
	Vireonidae	2	4	19.3	86.30%	0.517	0,1006; 0,3381	<0,0001

Note. τ²: variance between studies. I²: percentage of variability due to heterogeneity.

PCR – pooled prevalence by parasite genus

The pooled prevalence estimates for the different parasite genera detected by PCR were: Haemoproteus: P= 14.2% (I² = 97.3%, τ² = 2.5006), Plasmodium: P= 11.6% (I² = 97.3%, τ² = 2.7022), and Leucocytozoon: P= 10.0% (I² = 98.4%, τ² = 4.0814). The test for subgroup differences showed no significant differences (Q = 3.93; df = 2; p = 0.1404) (Table 1).

PCR – pooled prevalence by bird family

The prevalence of haemosporidian infections varied widely among bird families. Some families showed notably high prevalence values, such as Monarchidae (monarch flycatchers; P = 81.0%), Strigidae (owls; P = 72.9%), and Meropidae (bee-eaters; P = 61.3%), while others, such as Charadriidae (plovers; P = 0.2%) and Spheniscidae (penguins; P = 0.6%), presented very low values. Heterogeneity was high in most cases (I² > 90%). In contrast, families such as Alaudidae (larks and calandrias), Charadriidae, and Strigidae showed null or very low heterogeneity. Subgroup analysis revealed significant differences in infection prevalence among bird families (Q = 2135.58; df = 71; p < 0.001) (Table 1).

Microscopy

Fifty-one studies used microscopy, with an estimated pooled prevalence of P= 13.1% (95% CI: 0.1034–0.1615), showing high heterogeneity (I² = 97.9%, τ² = 3.24) (Table 1).

Microscopy – pooled prevalence by continent

The estimated prevalence by continent was P= 22.3% in Africa (I² = 95.5%), P= 28.5% in Europe (I² = 96.9%), P = 8.8% in the Americas (I² = 98.2%), P= 15.7% in Asia (I² = 96.0%), and P= 9.1% in Oceania (no heterogeneity estimated as only one study was available). These differences in point estimates were statistically significant (Q = 19.76; df = 4; p = 0.0006) (Table 1).

Microscopy – pooled prevalence by parasite genus

Regarding parasite genera detected through microscopy, the following prevalence estimates were observed: Haemoproteus P= 23.2% (I² = 97.3%, τ² = 1.473), Plasmodium P= 9.8% (I² = 96.2%, τ² = 2.066), and Leucocytozoon P= 6.2% (I² = 98.9%, τ² = 7.260). The test for subgroup differences was statistically significant (Q = 25.12; df = 2; p < 0.0001), indicating that prevalence estimates differed among parasite genera (Table 1).

Microscopy – pooled prevalence by bird family

The prevalence of haemosporidian infections varied widely among bird families evaluated by microscopy. Some families showed very high prevalence estimates, such as Laniidae (shrikes, P= 92.2%), Hirundinidae (swallows, P= 47.0%), and Passerellidae (new world sparrows, P= 47.5%), while others, such as Grallariidae (antpittas, P= 0.1%), Troglodytidae (wrens, P= 0.4%), and Furnariidae (ovenbirds, P= 0.6%), exhibited very low values. Heterogeneity across studies was high (I² > 90%) in most families, such as Thraupidae (tanagers, 99.1%), Hirundinidae (99.7%), and Trochilidae (hummingbirds, 98.7%). However, some families showed low or null heterogeneity, such as Phylloscopidae (leaf warblers, I² = 0%). Subgroup analysis revealed statistically significant differences in infection prevalence among bird families (Q = 410.28; df = 41; p < 0.0001).

Meta-regression

Of the 181 studies included in the meta-analysis, 84 contained sufficient information to be incorporated into the environmental meta-regression analysis. Of these, 64 studies reported explicit geographic coordinates, while 20 reported the sampling site as georeferenced to a clearly identifiable locality. Regarding environmental variables, 11 studies provided temperature data and 15 reported altitude or altitudinal ranges.

In the meta-regression analyses performed, no significant associations were observed between year of publication and estimated prevalence, for both PCR (β = −0.0049; p = 0.1467) and microscopy (β = −0.0016; p = 0.5963) (Figure 3(a) and (b), respectively). No significant associations were found between prevalence and environmental variables: altitude (β = 0.0003; p = 0.9584), latitude (β = −0.0772; p = 0.5387), and temperature (β = 0.0055; p = 0.6637) (Figures 4(a) and (b), and 5).

Figure 3.

Meta-regression of prevalence in relation to the year of publication of the studies, according to diagnostic method: (a) PCR and (b) microscopy.

Figure 4.

Meta-regression of prevalence in relation to geographic variables: (a) latitude and (b) altitude (m a.s.l.).

Figure 5.

Meta-regression of prevalence in relation to mean annual temperature.

Sensitivity analysis

Upon removing the influential studies (61) identified in the sensitivity analysis, no significant changes were observed in the overall prevalence or in the prevalence obtained from the subgroup analysis. Additionally, no changes were observed in the heterogeneity of the studies included in these meta-analysis.

Discussion

This is the first systematic review and meta-analysis of the global prevalence of haemosporidian parasites in wild birds based on prevalence estimates obtained using microscopy and PCR. The systematic review included 206 studies that achieved acceptable methodological quality, from which the prevalence was synthesized. The included studies were published between 1982 and 2024, in Spanish, English, and Portuguese, and comprised data from 135 bird families. The meta-analysis showed that the global prevalence of infection was P=12% by PCR and P=13% by microscopy.

The results of the methodological quality assessment, based on an adaptation of the Joanna Briggs Institute criteria²², revealed frequent weaknesses in the included studies. One of these was the limited description of the sampling environment. Although most studies reported geographic coordinates or the general name of the sampling site, few provided detailed information about the habitat, ecological conditions (forest type, temperature, humidity, access to water sources, topography, among others), or characteristics of the bird community sampled, which limits the interpretation of environmental factors associated with prevalence. Statistical procedures were also often not clearly detailed; many studies reported prevalence values without explaining the formula used or providing the number of individuals sampled and positive, which limited traceability and reproducibility when manually calculating prevalence.

The concentration of studies with samples collected and developed in countries such as the United States and Brazil likely reflects not only institutional and logistical capacity to conduct research with wild birds but also access to natural populations and infrastructure for blood sample processing. In South America, Brazil stands out for its research tradition and technical capabilities, which have promoted scientific output in this field³⁵. In addition to Brazil, Ecuador and Colombia are biodiversity hotspots, favoring the study of a wide range of host–parasite interactions^6,36. However, although Colombia has the highest bird diversity in the world³⁷ and its ecosystems are suitable for investigating parasite ecological dynamics^38,39, this review identified only eight studies with samples from this country, seven of which were processed locally. This suggests that research development depends not only on biological richness but also on factors such as research priorities, available scientific infrastructure, and the geographic distribution of birds.

The high heterogeneity observed in the meta-analysis indicates significant variability among the included studies. This heterogeneity can be attributed to geographic, taxonomic, and methodological factors. Ecologically and geographically, the studies encompassed a wide range of regions with distinct environmental conditions that influence the distribution and transmission of haemosporidians⁴⁰. The taxonomic diversity of host birds also plays a role, as species differ in behavior, physiology, and evolutionary history, which can impact their susceptibility to infection^1,41. Regarding methods, studies employed different diagnostic approaches (PCR, microscopy, or both), with variations in protocols, sample type and quality, and technical expertise, which significantly affected detection capacity and specificity⁴². For example^43, demonstrated that poorly prepared or stained blood smears can lead to significant underestimations in microscopy, while PCR detection capacity may vary depending on sample volume, type, and extraction protocol⁴⁴. Furthermore, prevalence is influenced by the time of year samples are collected, as parasitemia may fluctuate according to the birds’ reproductive cycle¹.

In this review, Haemoproteus was the most prevalent genus in studies using both microscopy and PCR, consistent with previous research that has demonstrated its higher detectability compared to other genera. One possible explanation is that Haemoproteus often reaches higher parasitemias than Plasmodium, facilitating detection by both diagnostic methods even in chronic or low-intensity infections^9,40,45,46. For example, Musa et al.⁴⁰ consistently observed high detection rates of Haemoproteus using microscopy, multiplex PCR, and nested PCR, thereby reinforcing the idea that this genus is easily detectable regardless of the method employed. Additionally, Haemoproteus exhibits notable host specificity^3,41, with a higher prevalence in species characterized by particular ecological traits, such as insectivorous habits, forested habitats, and restricted distributions⁴¹. These factors suggest that both parasite and host characteristics influence higher prevalence values, which may also explain the high heterogeneity observed in family-level analysis.

Examining bird families with the highest estimated prevalence of haemosporidian parasites, no consistent patterns were observed. In PCR analysis, the families with the highest estimated prevalence included Nectariniidae (sunbirds and spider hunters, P= 22.5%, 10 studies), Hirundinidae (P= 19.8%, 10), Emberizidae (sparrows and buntings, P= 18.6%, 19), Passerellidae (old world sparrows, P= 19.2%, 16), and Paridae (chickadees, P= 17.2%, 36). For microscopy, the highest prevalence values were observed in Columbidae (pigeons, P= 40.3%, 9 studies) and Nectariniidae (P= 31.8%, 9 studies). Methodological studies suggest that for robust meta-analysis estimates, at least five studies are required, preferably more than nine, since including only the nine largest studies can reproduce up to 80% of the results of a complete meta-analysis^47,48. Therefore, these families with ≥9 studies can be considered sufficiently represented to interpret prevalence estimates as robust. However, although these criteria improve statistical robustness, they may present ecological limitations, especially in highly diverse Neotropical communities, where many species are represented by small sample sizes⁴⁹. The underrepresentation of species could obscure community-level processes, such as dilution or the dynamics of prevalence amplification^50–53.

Prevalence values varied across continents depending on the diagnostic method employed. However, considering each method separately, Africa (PMIC = 22.3%; PPCR = 13.5%) and Europe (PMIC = 28.6%; PPCR = 12.6%) showed the highest estimates compared to other continents (Table 1). This result may be influenced by factors such as a long tradition in avian parasitology studies, which has promoted the use of standardized protocols, highly trained personnel, and high-quality blood smears, conditions that improve microscopy detection⁴³. It is essential to note that not all studies employed both diagnostic methods; some used only microscopy, while others utilized both techniques. This methodological variability may affect the direct comparability between regions and lead to an underestimate or overestimate of the true prevalence when data are pooled.

The prevalence of haemosporidian parasite infection by genus estimated using PCR in this review was PPla=11.6% for Plasmodium, PHae= 14.2% for Haemoproteus, and PLeu= 10.0% for Leucocytozoon. These values differ from those reported by Swangneat et al.¹⁷, who reported PPla = 21%, PHae= 18%, and PLeu= 34%, respectively, in wild and domestic birds from Southeast Asia. The higher prevalences observed by Swangneat et al.¹⁷ could be attributed to: (1) inclusion of only 15 studies, whereas this review analyzed 136 PCR-based studies; (2) focus on a single geographic region that may favor haemosporidian transmission due to ecological characteristics; and (3) the search for parasites was extended to domestic birds. This latter aspect is especially relevant for Leucocytozoon, as much of the reported prevalence is influenced by the study of Khumpim et al.⁵⁴, documenting 81% prevalence in domestic birds. In comparison, Yan et al.¹⁷ reported PPla= 12.8% in wild birds, slightly higher than the estimate obtained in this study (PPla= 11.58%). Differences may arise from inclusion criteria, as Yan et al.¹⁷ considered only studies with sample sizes >400 individuals, which could affect general prevalence estimates.

Comparisons with captive wild birds show that the prevalences estimated here are similar or lower. Research in zoos and rehabilitation centers reports variable prevalence values (7%<P<30%), depending on parasite genus, diagnostic method, and host species. For example, in Brazilian zoo birds, P= 12.6% predominated by Plasmodium⁵⁵; in penguins from Japanese facilities, PPla= 7.5% and PHae= 1.7% ⁵⁷; in rehabilitated raptors in Iran, PHae= 26.7% and PLeu= 10%⁵⁶; and in rescued birds in Portugal, overall prevalence reached P= 30.3% using PCR⁵⁷. These data suggest that while captivity may facilitate parasite transmission due to host density and open facilities^55,58, infection prevalence values are comparable to or exceed those observed in free-living wild bird populations.

This review has some limitations. First, only studies published in English, Spanish, and Portuguese were included, potentially excluding relevant research in other languages and limiting the comprehensiveness of the review. Environmental variables, such as temperature and altitude, were inconsistently reported across studies. When they were unavailable, geographic coordinates were used to extract altitude (SRTM) and mean annual temperature (WorldClim 2.1). While this approach allowed for data standardization, it may have introduced bias, as WorldClim provides long-term average climatic values rather than the actual temperature at the time of sampling. Consequently, this limitation could have influenced the observed relationships between altitude, temperature, and prevalence.

Finally, the MalAvi database was not considered as a source of information, even though 52.85% of the total references indexed in it were retrieved from the databases included in the review. The references not retrieved use laboratory tests or assays for parasite identification; others focus on studying vectors and transmission, as well as other relevant aspects different from those considered in the search strategy of this review.

Based on this review, we recommend that future studies on haemosporidian prevalence in birds include the precise geographic coordinates of sampling sites, the month or season of sampling, environmental variables such as temperature and altitude, a description of the habitat or ecosystem type, the total number of individuals sampled, the number of infected individuals, as well as overall prevalence and, when possible, prevalence by parasite species. This will facilitate reproducibility and comparability among primary studies, as well as the combining and synthesizing of their findings in future reviews of this nature.

Finally, the results of this systematic prevalence review provide a global estimate of population-level infection by haemosporidian parasites in wild birds, representing a valuable contribution to understanding the distribution and frequency of these parasites worldwide. Our findings identified bird taxonomic groups and continents with particularly high prevalence estimates, which can guide future research and conservation actions. Furthermore, the results highlight the importance of considering host, vector, and environmental characteristics in parasitic ecology studies, while also indicating gaps in some geographic regions, such as Paraguay, French Guiana, and post-Soviet states. This synthesis helps delineate monitoring priorities in studying host–parasite dynamics in wild birds.

Conclusion

This review provides a global overview of the prevalence distribution of haemosporidian parasites of the genera Plasmodium, Haemoproteus, and Leucocytozoon in wild birds, based on data obtained from blood samples. Plasmodium was the most prevalent genus, followed by Haemoproteus and Leucocytozoon. It is possible to estimate this parameter at different scales, including continent, country, bird family, and parasite genus. This approach enables the identification of regions, bird families, and parasite species with the highest prevalence, providing valuable information to prioritize future studies that guide avifaunal conservation efforts and epidemiological monitoring. Furthermore, publication year was not associated with prevalence estimates according to diagnostic method, and geographic (latitude and altitude) and environmental variables (temperature) were also not significantly associated with prevalence. No single variable was identified that could explain the observed variation. Instead, high heterogeneity among studies was observed, suggesting that multiple biological, environmental, and methodological factors contribute to the differences and should be considered in future analysis and comparisons.

Supplemental material

Supplemental material - Global prevalence of haemosporidian parasites in wild birds: Systematic review and meta-analysis

Supplemental material for Global prevalence of haemosporidian parasites in wild birds: Systematic review and meta-analysis by Tiana Glemarjenni Beltran Toledo, Leidy Johanna Rueda Díaz and Fernando Rondón González in Avian Biology Research

Supplemental material

Supplemental material - Global prevalence of haemosporidian parasites in wild birds: Systematic review and meta-analysis

Supplemental material

Supplemental material - Global prevalence of haemosporidian parasites in wild birds: Systematic review and meta-analysis

Footnotes

ORCID iDs

Tiana Glemarjenni Beltran Toledo

Leidy Johanna Rueda Díaz

Fernando Rondón González

Author contributions

Conceptualization: Tiana Glemarjenni Beltran Toledo, Leidy Johanna Rueda Díaz and Fernando Rondón González.; methodology: Tiana Glemarjenni Beltran Toledo, Leidy Johanna Rueda Díaz and Fernando Rondón González.; validation: Leidy Johanna Rueda Díaz; formal analysis: Tiana Glemarjenni Beltran Toledo, Leidy Johanna Rueda Díaz and Fernando Rondón González.; investigation: Tiana Glemarjenni Beltran Toledo and Leidy Johanna Rueda Díaz.; resources: Tiana Glemarjenni Beltran Toledo, Leidy Johanna Rueda Díaz and Fernando Rondón González.; data curation: Tiana Glemarjenni Beltran Toledo and Leidy Johanna Rueda.; writing—original draft preparation: Tiana Glemarjenni Beltran Toledo, Leidy Johanna Rueda Díaz.; writing—review and editin: Tiana Glemarjenni Beltran Toledo, Leidy Johanna Rueda Díaz and Fernando Rondón González.; visualization: Tiana Glemarjenni Beltran Toledo and Leidy Johanna Rueda Díaz.; supervision: Fernando Rondón González.; project administration: Leidy Johanna Rueda Díaz.; funding acquisition: Fernando Rondón González. All authors have read and agreed to the published version of the manuscript. Please turn to the for the term explanation. Authorship must be limited to those who have contributed substantially to the work reported.

Funding

This research was funded by Vicerrectoría de Investigación y Extensión, Universidad Industrial de Santander; VIE-UIS 3707.

Declaration of conflicting interests

The authors declare no conflicts of interest.

Supplemental material

Supplemental material for this article is available online.

References

Valkiūnas

Avian malaria parasites and other haemosporidia. Boca Raton (FL): CRC Press; 2005.

Atkinson

Van Riper

. Pathogenicity and epizootiology of avian haematozoa: Plasmodium, Leucocytozoon, and Haemoproteus. In: Loye

Zuk

, editors. Bird-parasite interactions: Ecology, evolution, and behaviour. Oxford: Oxford University Press; 1991. pp. 19–48.

Beadell

Covas

Gebhard

Ishtiaq

Melo

Schmidt

Perkins

Graves

Fleischer

. Host associations and evolutionary relationships of avian blood parasites from West Africa. Int J Parasitol. 2009;39(3):257–266.

Atkinson

LaPointe

. Introduced avian diseases, climate change, and the future of Hawaiian honeycreepers. J Avian Med Surg. 2009;23(1):53–63.

Atkinson

Samuel

. Avian malaria Plasmodium relictum in native Hawaiian forest birds: Epizootiology and demographic impacts on Apapane Himatione sanguinea. J Avian Biol. 2010;41(4):357–366.

Sebaio

Braga

ÉM

Branquinho

Fecchio

Marini

MÂ

. Blood parasites in Brazilian Atlantic Forest birds: Effects of fragment size and habitat dependency. Bird Conserv Int 2010;20(4): 432–439.

Asghar

Hasselquist

Hansson

Zehtindjiev

Westerdahl

Bensch

. Hidden costs of infection: Chronic malaria accelerates telomere degradation and senescence in wild birds. Science. 2015;347(6220):436–438.

Moreno

López

Corcho

. Principales medidas en epidemiología. Salud Publica Mex. 2000;42(4):338–344.

Asghar

Hasselquist

Bensch

. Are chronic avian haemosporidian infections costly in wild birds? J Avian Biol. 2011;42(6):530–537.

10.

Keesing

Belden

Daszak

Dobson

Harvell

Holt

, et al. Impacts of biodiversity on the emergence and transmission of infectious diseases. Nature. 2010;468(7324):647–652.

11.

LaPointe

Atkinson

Samuel

. Ecology and conservation biology of avian malaria. Ann N Y Acad Sci. 2012;1249(1):211–226.

12.

Lotta

Pacheco

Escalante

González

Mantilla

Moncada

Adler

Matta

. Leucocytozoon diversity and possible vectors in the Neotropical highlands of Colombia. Protist. 2016;167(2):185–204.

13.

Ishtiaq

Barve

. Do avian blood parasites influence hypoxia physiology in a high elevation environment? BMC Ecol 2018;18:15.

14.

De Angeli Dutra

Fecchio

Martins Braga

Poulin

. Migratory birds have higher prevalence and richness of avian haemosporidian parasites than residents. Int J Parasitol. 2021;51(10):877–882. doi: 10.1016/j.ijpara.2021.03.001.

15.

Ellis

Fecchio

Ricklefs

. Haemosporidian parasites of Neotropical birds: Causes and consequences of infection. Auk. 2020;137(4):1–16.

16.

Ndlovu

Wardjomto

Pori

Nangammbi

. Diversity and host specificity of avian haemosporidians in an Afrotropical conservation region. Animals. 2024;14(19): 2906.

17.

Yan

Sun

Zhao

Hou

Zhang

Zhao

, et al. Global prevalence of Plasmodium infection in wild birds: A systematic review and meta-analysis. Res Vet Sci. 2024;168: 105136. doi: 10.1016/j.rvsc.2024.105136.

18.

Swangneat

Srikacha

Soulinthone

Paudel

Srisanyong

Stott

, et al. Molecular prevalence of avian haemosporidian parasites in Southeast Asia: Systematic review and meta-analysis. Animals. 2025;15(5): 636.

19.

Samuel

Liao

Atkinson

LaPointe

. Facilitated adaptation for conservation – Can gene editing save Hawaii’s endangered birds from climate-driven avian malaria? Biol Conserv. 2020;241:108390.

20.

Santiago-Alarcon

Marzal

. Research on avian haemosporidian parasites in the tropics before the year 2000. In: Santiago-Alarcon

Marzal

, editors. Avian malaria and related parasites in the tropics: Ecology, evolution and systematics. Cham: Springer; 2020. pp. 1–44.

21.

Peters

MDJ

Marnie

Tricco

Pollock

Munn

Alexander

, et al. Updated methodological guidance for the conduct of scoping reviews. JBI Evid Synth. 2020;18(10): 2119–2126.

22.

Munn

Moola

Lisy

Riitano

Tufanaru

. Chapter 5: Systematic reviews of prevalence and incidence. In: Aromataris

Munn

, editors. JBI manual for evidence synthesis. 2020 [cited 2025 Oct 13]. Available from: https://synthesismanual.jbi.global

23.

Ouzzani

Hammady

Fedorowicz

Elmagarmid

. Rayyan: A web and mobile app for systematic reviews. Syst Rev. 2016;5: 210.

24.

Higgins

JPT

Thomas

Chandler

Cumpston

Page

Welch

, editors. Cochrane handbook for systematic reviews of interventions. 2nd ed. Chichester: Wiley; 2019.

25.

Serdar

Cihan

Yücel

Serdar

. Sample size, power, and effect size revisited: Simplified and practical approaches in pre-clinical, clinical, and laboratory studies. Biochem Med (Zagreb) 2021;31(1): 27–53.

26.

Higgins

JPT

Thompson

Deeks

Altman

. Measuring inconsistency in meta-analyses. BMJ. 2003;327(7414):557–560.

27.

Balduzzi

Rücker

Schwarzer

. How to perform a meta-analysis with R: a practical tutorial. Evid Based Ment Health. 2019;22:153–160.

28.

Viechtbauer

. Conducting meta-analyses in R with the metafor package. J Stat Softw. 2010;36(3):1–48.

29.

West

Gartlehner

Mansfield

Poole

Tant

Lenfestey

, et al. Comparative effectiveness review methods: Clinical heterogeneity (Methods Research Paper, AHRQ Publication No. 10-EHC070-EF). Rockville (MD): Agency for Healthcare Research and Quality; 2010.

30.

Farr

Rosen

Caro

Crippen

Duren

Hensley

, et al. The Shuttle Radar Topography Mission. Rev Geophys. 2007;45(2):RG2004.

31.

Fick

Hijmans

. WorldClim 2: New 1-km spatial resolution climate surfaces for global land areas. Int J Climatol. 2017;37(12):4302–4315.

32.

QGIS Development Team . QGIS Geographic Information System. Version 3.34.12. Open Source Geospatial Foundation; 2024. Available from: https://www.qgis.org

33.

Hunter

Saratzis

Sutton

Boucher

Sayers

Bown

. In meta-analyses of proportion studies, funnel plots were found to be an inaccurate method of assessing publication bias. J Clin Epidemiol. 2014;67(8):897–903.

34.

Borenstein

. Common mistakes in meta-analysis and how to avoid them. Englewood, NJ: Biostat; 2019.

35.

Clark

Clegg

Lima

. A review of global diversity in avian haemosporidians (Plasmodium and Haemoproteus): New insights from molecular data. Int J Parasitol. 2014;44(5):329–338.

36.

Myers

Mittermeier

da Fonseca

Kent

. Biodiversity hotspots for conservation priorities. Nature. 2000;403(6772):853–858.

37.

Montoya

Gonzalez

Tenorio

López-Ordóñez

Pinto Gómez

Cueva

, et al. A morphological database for 606 Colombian bird species. Ecology. 2018;99(7):1693.

38.

González

Matta

Ellis

Miller

Ricklefs

Gutiérrez

. Mixed species flock, nest height, and elevation partially explain avian haemoparasite prevalence in Colombia. PLoS ONE. 2014;9(6):e100695.

39.

González-Quevedo

Pabón

Avendaño

Vásquez

. Prevalence of haemosporidians in a Neotropical endemic bird area. Parasitology. 2016;143(9):1223–1230.

40.

Musa

Ahlstrand

Hellgren

Äng

Isaksson

Bensch

. Untangling the actual infection status: Detection of avian haemosporidian parasites of three Malagasy bird species using microscopy, multiplex PCR, and nested PCR methods. Int J Parasitol Parasites Wildl. 2022;17:234–243.

41.

Laurance

SGW

Jones

Westcott

McKeown

Harrington

Hilbert

. Habitat fragmentation and ecological traits influence the prevalence of avian blood parasites in a tropical rainforest landscape. PLoS ONE. 2013;8(10):e76227.

42.

Krams

Suraka

Cīrule

Hukkanen

Tummeleht

Mierauskas

Rytkönen

Rantala

Vrublevska

Orell

. A comparison of microscopy and PCR diagnostics for low-intensity infections of haemosporidian parasites in the Siberian tit Poecile cinctus. Ann Zool Fenn. 2012;49(5–6):331–340.

43.

Valkiūnas

Iezhova

Krizanauskienė

Palinauskas

Sehgal

RNM

Bensch

. A comparative analysis of microscopy and PCR-based detection methods for blood parasites. J Parasitol. 2008;94(6): 1395–1401.

44.

Cheng

Huang

Liang

. The effect of blood sample preservation methods on the detection of avian haemosporidian parasites by PCR. Parasitol Res. 2015;114(9):3287–3292.

45.

Fallon

Ricklefs

. Parasitemia in PCR-detected Plasmodium and Haemoproteus infections in birds. J Avian Biol. 2008;39(5):514–522.

46.

Mukhin

Palinauskas

Platonova

Kobylkov

Vakoliuk

, et al. The strategy to survive primary malaria infection: An experimental study on behavioural changes in parasitized birds. PLoS ONE. 2016;11(7):e0159216.

47.

Borenstein

Hedges

Higgins

JPT

Rothstein

. Introduction to meta-analysis. Chichester: John Wiley & Sons; 2009.

48.

McLellan

Perera

. Restricted meta-analyses versus full meta-analyses: Threshold number of studies based on study sample size. BMJ Evid Based Med. 2018;23(Suppl 2):A10.

49.

Yamaura

Kéry

Royle

. Study of biological communities subject to imperfect detection: bias and precision of community N-mixture abundance models in small-sample situations. Ecol Res 2016;31:1–10.

50.

Halliday

Rohr

Laine

. Biodiversity loss underlies the dilution effect of biodiversity. Ecol Lett. 2020;23:1611–1622.

51.

Keesing

Ostfeld

. Dilution effects in disease ecology. Ecol Lett. 2021;24(11):2490–2505.

52.

Ferragutti

Martínez-de la Puente

Bensch

Roiz

Ruiz

Viana

, et al. A field test of the dilution effect hypothesis in four avian multi-host pathogens. PLoS Pathog. 2021;17(1):e1009637.

53.

Tamayo-Quintero

Martínez-de la Puente

San-José

González-Quevedo

Rivera-Gutiérrez

. Bird community effects on avian malaria infections. Sci Rep. 2023;13:11681.

54.

Khumpim

Chawengkirttikul

Junsiri

Watthanadirek

Poolsawat

Minsakorn

Srionrod

Anuracpreeda

. Molecular detection and genetic diversity of Leucocytozoon sabrazesi in chickens in Thailand. Sci Rep. 2021;11(1):16686.

55.

Chagas

CRF

Valkiūnas

de Oliveira Guimarães

Monteiro

Guida

FJV

Simões

Rodrigues

de Albuquerque Luna

Kirchgatter

. Diversity and distribution of avian malaria and related haemosporidian parasites in captive birds from a Brazilian megalopolis. Malar J. 2017;16:83.

56.

Nourani

Aliabadian

Mirshamsi

Dinparast Djadid

. Prevalence of co-infection and genetic diversity of avian haemosporidian parasites in two rehabilitation facilities in Iran: Implications for the conservation of captive raptors. BMC Ecol Evol 2022;22: 114.

57.

Cruz

de Carvalho

Ferreira

Nunes

Casero

Marzal

. Avian haemosporidian infection in wildlife rehabilitation centres of Portugal: Causes, consequences, and genetic diversity. Animals (Basel) 2024;14(8):1216.

58.

Inumaru

Shimizu

Shibata

Murata

Sato

. The difficulties of ex situ conservation: A nationwide investigation of avian haemosporidia among captive penguins in Japan. J Zool Bot Gard. 2025;6(1):7.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.10 MB

0.00 MB

0.06 MB

0.11 MB