Spatial distribution of Giardia lamblia infection among general population in Mazandaran Province, north of Iran

Human Giardiasis in Ghana - A Scoping Review of Studies From 2004 to 2024

Background and Aim

Human giardiasis poses a significant public health challenge globally, particularly in resource-limited countries due to poor personal hygiene, environmental sanitation, and unsafe water. It affects approximately 300 million people globally every year, and children are the most at-risk population. This scoping review assesses the burden, transmission dynamics, and public health implications of human giardiasis in Ghana.

Methods

A comprehensive search strategy across PubMed, African Journals Online, Science Direct, Scopus and Web of Science databases using key terms "Giardia duodenalis," "Giardia intestinalis," and "Giardiasis." Published articles on Human giardiasis in Ghana between 2004 and 2024 on epidemiology, prevalence, diagnostic methods, and target populations were extracted.

Results

Seventeen studies conducted in Ghana met the inclusion criteria and were included in this review. The prevalence of Giardia duodenalis in Ghana varies significantly across studies and settings, with rates ranging from 0.7% to 59.6%, with children being the most affected. However, studies conducted in Ghana since 2020 indicate a lower prevalence, with rates between 0.7% and 13.0%. Regional studies indicate varied prevalence: 0.7%-13.0%, 2.3%-59.6%, and 5.9% in the Southern, Middle, and Northern belts, respectively.

Conclusion

The prevalence of human giardiasis in Ghana is relatively low. However, targeted public health interventions are necessary to maintain the progress achieved, in addition to improvements in sanitation and hygiene practices.

Occurrence and assemblage distribution of Giardia Duodenalis in symptomatic and asymptomatic patients in southeastern Iran (2019-2022)

BACKGROUND

The ubiquitous protozoan parasite Giardia duodenalis is a major contributor to the global burden of diarrhoea, particularly in young children living in poor-resource regions. Although rarely mortal, giardiasis is associated with growth retardation and cognitive impairment in early childhood. Here we investigate the epidemiology of human giardiasis in Iranshahr (south-eastern Iran), a region where this information was previously lacking.

METHODS

Stool samples were collected from 17,455 outpatients and inpatients attended at three major hospital settings during April 2020 and March 2022. Microscopy was used as a screening method for the presence of Giardia cysts, and the identification of G. duodenalis assemblages was carried out using PCR and Sanger sequencing.

RESULTS

The overall prevalence of giardiasis was 1.87 (326/17,455; 95% CI: 1.7-2.1). Being female was positively associated with higher odds of giardiasis (p = 0.014). Individuals without diarrhoea were less likely to have giardiasis (p = 0.022). Individuals attending the Iran Hospital were more likely to harbour G. duodenalis infections compared to those attending at the Khatam Hospital and the Clinical Reference Laboratory (p = 0.001). Our sequence analyses revealed the presence of assemblages A (56.5%, 13/23), B (39.1%, 9/23), and A + B (4.4%, 1/23). No association was observed between the occurrence of a given assemblage and the occurrence of diarhroea.

CONCLUSIONS

Giardia infections were found at relatively low prevalence rates in both symptomatic and asymptomatic individuals seeking medical attention. Being female, having diarrhoea, and being sampled during 2020-21 were predictors of giardiasis. Although limited, our molecular data indicate that some Giardia infections may be zoonotic in nature. These data should be corroborated and expanded in future epidemiological studies targeting simultaneously human, animal, and environmental (water) samples to improve our understanding of the epidemiology of giardiasis in Iran.

Spatio-temporal analysis and determination of the ecological niche model of Giardia Lamblia (Lambl, 1859) in Ardabil province, northwestern Iran

Intestinal parasites have a serious health problem and frequently infect children in poor urban areas in developing countries. Some types of Cryptosporidium, Entamoeba and Giardia are amongst the most prevalent ones. The aim of this study was explore the distribution pattern of intestinal parasites and the ecological niche of Giardia lamblia in Ardabil Province. This was retrospective cross-sectional study, the officially registered statistics of health centers and hospitals in Ardabil University of Medical Sciences from January 2017 to December 2019 were used. The Kriging interpolation analysis was run to detect the high-risk areas of the disease in the province (P < 0.05) by ArcGIS10.4.1 and to construct the ecological niche model of the G.lamblia parasite, analyzed by Maxent3.3 software. Totally of 238 cases of intestinal parasite were reported during the study period, 77.7% of which were males and 22.3% females. Seven types of intestinal parasites were prevalent with G.lamblia species (79.4%) being the most and Entamoeba histolytica species (4%) the least prevalent one. There was one hotspot in the province in the center with an incidence risk of 41-45.5%. The most important climate and environmental factors affecting the ecological niche of G.lamblia are Bio16, Bio3, and the NDVI. G.lamblia is the most prevalent intestinal parasite in Ardabil Province; moreover, one important hotspots was also detected in the province that can provide useful information regarding the management and control of this parasite.

Spatial Distribution of Common Pathogenic Human Intestinal Protozoa in Iran: A Systematic Review

Background:

Pathogenic intestinal protozoa are considered as a serious public health problem in developing countries. This study aimed to elucidate the overall prevalence and spatial distribution of three common human pathogenic intestinal protozoan infections in Iran.

Methods:

Six English and Persian databases were explored for published papers on the prevalence of Entamoeba histolytica/dispar, Giardia lamblia, and Cryptosporidium spp. in the general population of Iran from 2000 to 2015. All eligible data were collected using a pre-designed data extraction form, and the overall prevalence was estimated using a random-effects meta-analysis model. We used ArcMap for mapping the prevalence of the studied protozoa and clustering analysis.

Results:

Altogether, 118 eligible papers from 24 provinces of Iran were included and analyzed. The weighted prevalence of E. histolytica/dispar, G. lamblia, and Cryptosporidium spp. infection among Iranian general population were calculated 1.3% (95% CI 1.1–1.5%), 10.6% (95% CI 9.6–11.5%) and 2% (95% CI 1.5–2.5%), respectively.

Conclusion:

Our findings indicated human intestinal protozoan infections caused by E. histolytica/dispar, G. lamblia, and Cryptosporidium spp. have still public health importance in some parts of Iran.

Pathogen flows from on-site sanitation systems in low-income urban neighborhoods, Dhaka: A quantitative environmental assessment

BACKGROUND

Despite wide usage of on-site sanitation, there is limited field-based evidence on the removal or release of pathogens from septic tanks and other primary treatment systems, such as anaerobic baffled reactors (ABR). In two low-income areas in Dhaka, we conducted a cross-sectional study to explore pathogen loads discharged from commonly used on-site sanitation-systems and their transport in nearby drains and waterways.

METHODS

We collected samples of drain water, drain sediment, canal water, and floodwater from April-October 2019. Sludge, supernatant, and effluent samples were also collected from septic tanks and ABRs. We investigated the presence and concentration of selected enteric pathogens (Shigella, Vibrio cholerae (V. cholerae), Salmonella Typhi (S. Typhi), Norovirus Genogroup-II (NoV-GII), and Giardia) and presence of Cryptosporidium in these samples using quantitative polymerase chain reaction (qPCR).The equivalent genome copies (EGC) of individual pathogens were estimated in each sample by interpolation of the mean Ct value to the corresponding standard curve and the dilution factor for each sample type. Absolute quantification was expressed as log₁₀ EGC per 100 mL for the water samples and log₁₀ EGC per gram for the sediment samples.

RESULTS

Among all samples tested (N = 151), 89% were contaminated with Shigella, 68% with V. cholerae and NoV-GII, 32% with Giardia, 17% with S. Typhi and 6% with Cryptosporidium. A wide range of concentration of pathogens [range: mean log₁₀ concentration of Giardia = 0.74 EGC/100 mL in drain ultrafiltration samples to mean log₁₀ concentration of NoV-GII and Giardia = 7.11 EGC/100 mL in ABR sludge] was found in all environmental samples. The highest pathogen concentrations were detected in open drains [range: mean log₁₀ concentration = 2.50-4.94 EGC/100 mL], septic tank effluent [range: mean log₁₀ concentration = 3.32-4.65 EGC/100 mL], and ABR effluent [range: mean log₁₀ concentration = 2.72-5.13 EGC/100 mL].

CONCLUSIONS

High concentrations of pathogens (particularly NoV-GII, V.cholerae and Shigella) were frequently detected in environmental samples from two low-income urban neighbourhoods of Dhaka city. The numerous environmental exposure pathways for children and adults make these findings of public health concern. These results should prompt rethinking of how to achieve safe sanitation solutions that protect public health in dense low-income areas. In particular, improved management and maintenance regimes, further treatment of liquid effluent from primary treatment processes, and appropriate application of onsite, decentralised and offsite sanitation systems given the local context.

Comparing spatio-temporal distribution of the most common human parasitic infections in Iran over two periods 2007 to 2012 and 2013 to 2018: A systematic quantitative literature review

This study analyses the spatio-temporal trend of the prevalence of the four most prevalent parasitic diseases in Iran over two periods, 2007 to 2012 and 2013 to 2018, indicating high-risk and low-risk areas. Out of 19 126 articles, we selected 220 articles for data extraction and calculated the pooled prevalence for cutaneous leishmaniasis, human toxoplasmosis, giardiasis and blastocystosis for all 31 provinces in the country. Anselin local Moran's I was used to identify clusters and outliers in the prevalence rates. The mean prevalence of cutaneous leishmaniasis patients was found 35.12 per 100 000 in 2007 to 2012 but fell to 19.12 per 100 000 in the 2013 to 2018 period. The mean prevalence of acute and chronic toxoplasmosis was 2.36% and 32.5%, respectively, in 2007 to 2012, which changed to 2.28% and 31.14% in 2013 to 2018. The total prevalence of giardiasis declined from 9.8% in 2007 to 2012 to 4.8% in 2013 to 2018, while the mean prevalence of blastocystosis declined from 8.9% in 2007 to 2012 to 6.76% in the 2013 to 2018 period. There was only one high-high cluster in 2007 to 2012 and that was due to giardiasis, while there were two in 2013 to 2018, one for blastocystosis and one for chronic toxoplasmosis. The total prevalence of blastocystosis, giardiasis and cutaneous leishmaniasis in Iran has continually declined since 2007. In contrast, the prevalence of toxoplasmosis in pregnant Iranian women has not been changed. Iran's Midwest has more parasitic infections compared to the Mideast, which may be explained by the existence of vast deserts and consequently dry and hot climate in the latter part of the country.

Prediction mapping of human leptospirosis using ANN, GWR, SVM and GLM approaches

Background

Recent reports of the National Ministry of Health and Treatment of Iran (NMHT) show that Gilan has a higher annual incidence rate of leptospirosis than other provinces across the country. Despite several efforts of the government and NMHT to eradicate leptospirosis, it remains a public health problem in this province. Modelling and Prediction of this disease may play an important role in reduction of the prevalence.

Methods

This study aims to model and predict the spatial distribution of leptospirosis utilizing Geographically Weighted Regression (GWR), Generalized Linear Model (GLM), Support Vector Machine (SVM) and Artificial Neural Network (ANN) as capable approaches. Five environmental parameters of precipitation, temperature, humidity, elevation and vegetation are used for modelling and predicting of the disease. Data of 2009 and 2010 are used for training, and 2011 for testing and evaluating the models.

Results

Results indicate that utilized approaches in this study can model and predict leptospirosis with high significance level. To evaluate the efficiency of the approaches, MSE (GWR = 0.050, SVM = 0.137, GLM = 0.118 and ANN = 0.137), MAE (0.012, 0.063, 0.052 and 0.063), MRE (0.011, 0.018, 0.017 and 0.018) and R² (0.85, 0.80, 0.78 and 0.75) are used.

Conclusion

Results indicate the practical usefulness of approaches for spatial modelling and predicting leptospirosis. The efficiency of models is as follow: GWR > SVM > GLM > ANN. In addition, temperature and humidity are investigated as the most influential parameters. Moreover, the suitable habitat of leptospirosis is mostly within the central rural districts of the province.