Surveillance and response systems for elimination of tropical diseases: summary of a thematic series in Infectious Diseases of Poverty

Zhou, Xiao‐Nong; Yap, Peiling; Tanner, Marcel; Bergquist, Robert; Utzinger, Jürg

doi:10.1186/s40249-016-0144-7

Cited by 24 publications

(19 citation statements)

References 39 publications

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“…Use of models to find hotspots of urinary schistosomiasis of different intensities is necessary. This may assist in informing surveillance and response systems for the elimination and control of re-emerging tropical diseases such as schistosomiasis [ 43 – 46 ].…”

Section: Discussionmentioning

confidence: 99%

Using the hierarchical ordinal regression model to analyse the intensity of urinary schistosomiasis infection in school children in Lusaka Province, Zambia

Simoonga

Kazembe

2017

Infect Dis Poverty

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BackgroundUrinary schistosomiasis has been a major public health problem in Zambia for many years. However, the disease profile may vary in different locale due to the changing ecosystem that contributes to the risk of acquiring the disease. The objective of this study was to quantify risk factors associated with the intensity of urinary schistosomiasis infection in school children in Lusaka Province, Zambia, in order to better understand local transmission.MethodsData were obtained from 1 912 school children, in 20 communities, in the districts of Luangwa and Kafue in Lusaka Province. Both individual- and community-level covariates were incorporated into an ordinal logistic regression model to predict the probability of an infection being a certain intensity in a three-category outcome response: 0 = no infection, 1 = light infection, and 2 = moderate/heavy infection. Random effects were introduced to capture unobserved heterogeneity.ResultsOverall, the risk of urinary schistosomiasis was strongly associated with age, altitude at which the child lived, and sex. Weak associations were observed with the normalized difference vegetation index, maximum temperature, and snail abundance. Detailed analysis indicated that the association between infection intensities and age and altitude were category-specific. Particularly, infection intensity was lower in children aged between 5 and 9 years compared to those aged 10 to 15 years (OR = 0.72, 95% CI = 0.51–0.99). However, the age-specific risk changed at different levels of infection, such that when comparing children with light infection to those who were not infected, age was associated with a lower odds (category 1 vs category 0: OR = 0.71, 95% CI: 0.50–0.99), yet such a relation was not significant when considering children who were moderately or heavily infected compared to those with a light or no infection (category 2 vs category 0: OR = 0.96, 95% CI: 0.45–1.64). Overall, we observed that children living in the valley were less likely to acquire urinary schistosomiasis compared to those living in plateau areas (OR = 0.48, 95% CI: 0.16–0.71). However, category-specific effects showed no significant association in category 1 (light infection), whereas in category 2 (moderate/high infection), the risk was still significantly lower for those living in the valley compared to those living in plateau areas (OR = 0.18, 95% CI: 0.04–0.75).ConclusionsThis study demonstrates the importance of understanding the dynamics and heterogeneity of infection in control efforts, and further suggests that apart from the well-researched factors of Schistosoma intensity, various other factors influence transmission. Control programmes need to take into consideration the varying infection intensities of the disease so that effective interventions can be designed.Electronic supplementary materialThe online version of this article (doi:10.1186/s40249-017-0262-x) contains supplementary material, which is available to authorized users.

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Section: Discussionmentioning

confidence: 99%

Using the hierarchical ordinal regression model to analyse the intensity of urinary schistosomiasis infection in school children in Lusaka Province, Zambia

Simoonga

Kazembe

2017

Infect Dis Poverty

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“…In addition, laboratory-based pathogen diagnosis was conducted to find novel pathogens or variant strains [ 49 , 50 ]. In the meantime, a syndrome-based surveillance system has also been important in supporting the detection of variations in the intestinal pathogen spectrum and the emergence of the new pathogen or variant strain in China [ 50 , 51 ].…”

Section: Discussionmentioning

confidence: 99%

Emergence of human caliciviruses among diarrhea cases in southwest China

Zhang

Yin

et al. 2016

BMC Infect Dis

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BackgroundAcute diarrhea is one of the most serious problems in global public health that causes considerable morbidity and mortality worldwide. Human caliciviruses (HuCV) including norovirus (NoV, genogroup GI and GII) and sapovirus (SaV), is a leading cause of acute sporadic diarrhea in individuals across all age groups. However, few studies had been conducted clarifying the characteristics of HuCV in diarrhea cases across all age groups in China. Our study was aimed at assessing the HuCV-related diarrhea burden and NoV genotypes distribution in southwest China.MethodsThe study was conducted in four hospitals in Kunming city, Yunnan province, from June 2014 to July 2015. Stool specimens were collected from 1,121 diarrhea cases and 319 healthy controls in outpatient departments. Reverse transcription polymerase chain reaction (RT-PCR) was used to detect NoV (GI, GII) and SaV. Sequencing was applied to confirm the three viral infections and phylogenetic analysis was performed to determine their genotypes. A structured questionnaire was used to record the demographic information and clinical symptoms of subjects.ResultsHuCV was detected at an 11.0 % infection rate in 1,121 diarrhea cases and at 3.4 % rate in 319 non-diarrhea subjects (p < 0.0001, OR = 3.5, 95 % CI 1.8–6.5). The prevalence of the NoV genogroup GII and genotype GII.4 in diarrhea cases was significantly higher than that found in healthy controls (p < 0.0001, p = 0.018, respectively). NoV GII (n = 118, 10.5 %) was the most common HuCV subtype in diarrhea cases, followed by SaV (n = 3, 0.3 %) and NoV GI (n = 2, 0.2 %). Of 118 NoV GII strains isolated from diarrhea patients. GII.4 (n = 55, 46.6 %) was the predominant strain, followed by GII.3 (n = 28, 23.7 %), GII.12 (n = 25, 21.2 %), GII.17 (n = 8, 6.8 %), and GII.5 (n = 2, 1.7 %). Of the 55 GII.4 strains, the GII.4 Sydney 2012 variant had absolutely predominant prevalence (n = 52, 94.5 %), followed by the NoV GII.4-2006b variant (n = 3, 5.5 %). The GII.4 Orleans 2009 variant was not found in diarrhea cases of the study.ConclusionsNoV GII was the major genogroup and GII.4 was the most predominant strain detected in diarrhea patients. The GII.17 is an emergent variant in sporadic diarrhea and might become the predominant strain in diarrhea cases in the near future. Rapid, accurate detection kits need to be developed to help us find and treat NoV-associated diarrhea in clinical settings in a timely manner.

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“…The presence of this species in China and it potential expansion is important from a public health perspective as a potential transmitter of Schistosoma mansoni to mainland China where is only the endemic area for S. japonica (Collins et al, 2012;Zhou et al, 2016a). Yet, to date no studies have described the potential distribution of this snail in China.…”

Section: Introductionmentioning

confidence: 99%

Predicting the spatial distribution of Biomphalaria straminea, a potential intermediate host for Schistosoma mansoni, in China

Habib

Guo

et al. 2016

Geospat Health

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Schistosomiasis is one of the most prevalent parasitic diseases impacting human health in the tropics and sub-tropics. The geographic distribution of Schistosoma mansoni, the most widespread species, includes areas in Africa, the Middle East, South America and the Caribbean. Snails of the genus Biomphalaria act as intermediate host for S. mansoni. Biomphalaria straminea is not indigenous in China but was accidentally introduced to Hong Kong from South America and has spread to other habitats in the southern parts of the country. This species is known for its great dispersal capacity that highlights the importance of the snail as a potential host for S. mansoni in China. In this connection, although no such infection has been recorded in the field so far, the continuous expansion of China's projects in endemic areas of Africa and import of the infection via returning workers or visitors deserve attention. The purpose of this study was to map and predict the spatial distribution of B. straminea in China. Snail occurrence data were assembled and investigated using MaxEnt software, along with climatic and environmental variables to produce a predictive risk map. Of the environmental variables tested, the precipitation of warmest quarter was the most contribution factor for snail's spatial distribution. Risk areas were found in southeastern China and it is expected that they will guide policies and control programmes to potential areas area of snail abundance and used for spatial targeting of control interventions for this invasive species.

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Surveillance and response systems for elimination of tropical diseases: summary of a thematic series in Infectious Diseases of Poverty

Cited by 24 publications

References 39 publications

Using the hierarchical ordinal regression model to analyse the intensity of urinary schistosomiasis infection in school children in Lusaka Province, Zambia

Using the hierarchical ordinal regression model to analyse the intensity of urinary schistosomiasis infection in school children in Lusaka Province, Zambia

Emergence of human caliciviruses among diarrhea cases in southwest China

Predicting the spatial distribution of Biomphalaria straminea, a potential intermediate host for Schistosoma mansoni, in China

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