Microgeographic Heterogeneity of Border Malaria During Elimination Phase, Yunnan Province, China, 2011-2013

Assessing the risk of malaria local transmission and re-introduction in China from pre-elimination to elimination: A systematic review

Assessing the risk of malaria local transmission and re-introduction is crucial for the preparation and implementation of an effective elimination campaign and the prevention of malaria re-introduction in China. Therefore, this review aims to evaluate the risk factors for malaria local transmission and re-introduction in China over the period of pre-elimination to elimination. Data were obtained from six databases searched for studies that assessed malaria local transmission risk before malaria elimination and re-introduction risk after the achievement of malaria elimination in China since the launch of the NMEP in 2010, employing the keywords "malaria" AND ("transmission" OR "re-introduction") and their synonyms. A total of 8,124 articles were screened and 53 articles describing 55 malaria risk assessment models in China from 2010 to 2023, including 40 models assessing malaria local transmission risk (72.7%) and 15 models assessing malaria re-introduction risk (27.3%). Factors incorporated in the 55 models were extracted and classified into six categories, including environmental and meteorological factors (39/55, 70.9%), historical epidemiology (35/55, 63.6%), vectorial factors (32/55, 58.2%), socio-demographic information (15/26, 53.8%), factors related to surveillance and response capacity (18/55, 32.7%), and population migration aspects (13/55, 23.6%). Environmental and meteorological factors as well as vectorial factors were most commonly incorporated in models assessing malaria local transmission risk (29/40, 72.5% and 21/40, 52.5%) and re-introduction risk (10/15, 66.7% and 11/15, 73.3%). Factors related to surveillance and response capacity and population migration were also important in malaria re-introduction risk models (9/15, 60%, and 6/15, 40.0%). A total of 18 models (18/55, 32.7%) reported the modeling performance. Only six models were validated internally and five models were validated externally. Of 53 incorporated studies, 45 studies had a quality assessment score of seven and above. Environmental and meteorological factors as well as vectorial factors play a significant role in malaria local transmission and re-introduction risk assessment. The factors related to surveillance and response capacity and population migration are more important in assessing malaria re-introduction risk. The internal and external validation of the existing models needs to be strengthened in future studies.

Multidisciplinary Investigations of Sustained Malaria Transmission in the Greater Mekong Subregion

In the course of malaria elimination in the Greater Mekong Subregion (GMS), malaria epidemiology has experienced drastic spatiotemporal changes with residual transmission concentrated along international borders and the rising predominance of Plasmodium vivax. The emergence of Plasmodium falciparum parasites resistant to artemisinin and partner drugs renders artemisinin-based combination therapies less effective while the potential spread of multidrug-resistant parasites elicits concern. Vector behavioral changes and insecticide resistance have reduced the effectiveness of core vector control measures. In recognition of these problems, the Southeast Asian International Center of Excellence for Malaria Research (ICEMR) has been conducting multidisciplinary research to determine how human migration, antimalarial drug resistance, vector behavior, and insecticide resistance sustain malaria transmission at international borders. These efforts allow us to comprehensively understand the ecology of border malaria transmission and develop population genomics tools to identify and track parasite introduction. In addition to employing in vivo, in vitro, and molecular approaches to monitor the emergence and spread of drug-resistant parasites, we also use genomic and genetic methods to reveal novel mechanisms of antimalarial drug resistance of parasites. We also use omics and population genetics approaches to study insecticide resistance in malaria vectors and identify changes in mosquito community structure, vectorial potential, and seasonal dynamics. Collectively, the scientific findings from the ICEMR research activities offer a systematic view of the factors sustaining residual malaria transmission and identify potential solutions to these problems to accelerate malaria elimination in the GMS.

Epidemiologic Analysis of Efforts to Achieve and Sustain Malaria Elimination along the China-Myanmar Border

Malaria cases have dramatically declined in China along the Myanmar border, attributed mainly to adoption of the 1-3-7 surveillance and response approach. No indigenous cases have been reported in China since 2017. Counties in the middle and southern part of the border area have a higher risk for malaria importation and reestablishment after elimination.

Polymorphism of Antifolate Drug Resistance in Plasmodium vivax From Local Residents and Migrant Workers Returned From the China-Myanmar Border

Drug-resistant Plasmodium vivax malaria impedes efforts to control, eliminate, and ultimately eradicate malaria in Southeast Asia. P. vivax resistance to antifolate drugs derives from point mutations in specific parasite genes, including the dihydropteroate synthase (pvdhps), dihydrofolate reductase (pvdhfr), and GTP cyclohydrolase I (pvgch1) genes. This study aims to investigate the prevalence and spread of drug resistance markers in P. vivax populating the China-Myanmar border. Blood samples were collected from symptomatic patients with acute P. vivax infection. Samples with single-clone P. vivax infections were sequenced for pvdhps and pvdhfr genes and genotyped for 6 flanking microsatellite markers. Copy number variation in the pvgch1 gene was also examined. Polymorphisms were observed in six different codons of the pvdhps gene (382, 383, 512, 549, 553, and 571) and six different codons of the pvdhfr gene (13, 57, 58, 61, 99, 117) in two study sites. The quadruple mutant haplotypes 57I/L/58R/61M/117T of pvdhfr gene were the most common (comprising 76% of cases in Myitsone and 43.7% of case in Laiza). The double mutant haplotype 383G/553G of pvdhps gene was also prevalent at each site (40.8% and 31%). Microsatellites flanking the pvdhfr gene differentiated clinical samples from wild type and quadruple mutant genotypes (F_ST= 0.259-0.3036), as would be expected for a locus undergoing positive selection. The lack of copy number variation of pvgch1 suggests that SP-resistant P. vivax may harbor alternative mechanisms to secure sufficient folate.

Targeting Malaria Hotspots to Reduce Transmission Incidence in Senegal

In central Senegal, malaria incidence declined in response to scaling-up of control measures from 2000 to 2010 and has since remained stable, making elimination unlikely in the short term. Additional control measures are needed to reduce transmission. We simulated chemoprophylaxis interventions targeting malaria hotspots using a metapopulation mathematical model, based on a differential-equation framework and incorporating human mobility. The model was fitted to weekly malaria incidence from 45 villages. Three approaches for selecting intervention targets were compared: (a) villages with malaria cases during the low transmission season of the previous year; (b) villages with highest incidence during the high transmission season of the previous year; (c) villages with highest connectivity with adjacent populations. Our results showed that intervention strategies targeting hotspots would be effective in reducing malaria incidence in both targeted and untargeted areas. Regardless of the intervention strategy used, pre-elimination (1-5 cases per 1000 per year) would not be reached without simultaneously increasing vector control by more than 10%. A cornerstone of malaria control and elimination is the effective targeting of strategic locations. Mathematical tools help to identify those locations and estimate the impact in silico.

Spatial and spatio-temporal analysis of malaria cases in Zimbabwe

Background

Although effective treatment for malaria is now available, approximately half of the global population remain at risk of the disease particularly in developing countries. To design effective malaria control strategies there is need to understand the pattern of malaria heterogeneity in an area. Therefore, the main objective of this study was to explore the spatial and spatio-temporal pattern of malaria cases in Zimbabwe based on malaria data aggregated at district level from 2011 to 2016.

Methods

Geographical information system (GIS) and spatial scan statistic were applied on passive malaria data collected from health facilities and aggregated at district level to detect existence of spatial clusters. The global Moran’s I test was used to infer the presence of spatial autocorrelation while the purely spatial retrospective analyses were performed to detect the spatial clusters of malaria cases with high rates based on the discrete Poisson model. Furthermore, space-time clusters with high rates were detected through the retrospective space-time analysis based on the discrete Poisson model.

Results

Results showed that there is significant positive spatial autocorrelation in malaria cases in the study area. In addition, malaria exhibits spatial heterogeneity as evidenced by the existence of statistically significant (P < 0.05) spatial and space-time clusters of malaria in specific geographic regions. The detected primary clusters persisted in the eastern region of the study area over the six year study period while the temporal pattern of malaria reflected the seasonality of the disease where clusters were detected within particular months of the year.

Conclusions

Geographic regions characterised by clusters of high rates were identified as malaria high risk areas. The results of this study could be useful in prioritizing resource allocation in high-risk areas for malaria control and elimination particularly in resource limited settings such as Zimbabwe. The results of this study are also useful to guide further investigation into the possible determinants of persistence of high clusters of malaria cases in particular geographic regions which is useful in reducing malaria burden in such areas.

Malaria Risk Map Using Spatial Multi-Criteria Decision Analysis along Yunnan Border During the Pre-elimination Period

In moving toward malaria elimination, finer scale malaria risk maps are required to identify hotspots for implementing surveillance–response activities, allocating resources, and preparing health facilities based on the needs and necessities at each specific area. This study aimed to demonstrate the use of multi-criteria decision analysis (MCDA) in conjunction with geographic information systems (GISs) to create a spatial model and risk maps by integrating satellite remote-sensing and malaria surveillance data from 18 counties of Yunnan Province along the China–Myanmar border. The MCDA composite and annual models and risk maps were created from the consensus among the experts who have been working and know situations in the study areas. The experts identified and provided relative factor weights for nine socioeconomic and disease ecology factors as a weighted linear combination model of the following: ([Forest coverage × 0.041] + [Cropland × 0.086] + [Water body × 0.175] + [Elevation × 0.297] + [Human population density × 0.043] + [Imported case × 0.258] + [Distance to road × 0.030] + [Distance to health facility × 0.033] + [Urbanization × 0.036]). The expert-based model had a good prediction capacity with a high area under curve. The study has demonstrated the novel integrated use of spatial MCDA which combines multiple environmental factors in estimating disease risk by using decision rules derived from existing knowledge or hypothesized understanding of the risk factors via diverse quantitative and qualitative criteria using both data-driven and qualitative indicators from the experts. The model and fine MCDA risk map developed in this study could assist in focusing the elimination efforts in the specifically identified locations with high risks.

Spatiotemporal Trends of Malaria in Relation to Economic Development and Cross-Border Movement along the China-Myanmar Border in Yunnan Province

The heterogeneity and complexity of malaria involves political and natural environments, socioeconomic development, cross-border movement, and vector biology; factors that cannot be changed in a short time. This study aimed to assess the impact of economic growth and cross-border movement, toward elimination of malaria in Yunnan Province during its pre-elimination phase. Malaria data during 2011-2016 were extracted from 18 counties of Yunnan and from 7 villages, 11 displaced person camps of the Kachin Special Region II of Myanmar. Data of per-capita gross domestic product (GDP) were obtained from Yunnan Bureau of Statistics. Data were analyzed and mapped to determine spatiotemporal heterogeneity at county and village levels. There were a total 2,117 malaria cases with 85.2% imported cases; most imported cases came from Myanmar (78.5%). Along the demarcation line, malaria incidence rates in villages/camps in Myanmar were significantly higher than those of the neighboring villages in China. The spatial and temporal trends suggested that increasing per-capita GDP may have an indirect effect on the reduction of malaria cases when observed at macro level; however, malaria persists owing to complex, multi-faceted factors including poverty at individual level and cross-border movement of the workforce. In moving toward malaria elimination, despite economic growth, cooperative efforts with neighboring countries are critical to interrupt local transmission and prevent reintroduction of malaria via imported cases. Cross-border workers should be educated in preventive measures through effective behavior change communication, and investment is needed in active surveillance systems and novel diagnostic and treatment services during the elimination phase.

Spatial and demographic disparities in short stature among school children aged 7-18 years: a nation-wide survey in China, 2014

OBJECTIVES

To identify spatial disparities and demographic characteristics of short stature, we analysed the prevalence of short stature collected in a nationwide health survey.

SETTINGS

Data were obtained from the 2014 Chinese National Survey on Students Constitution and Health (a cross-sectional study of China). Participants came from 30 provinces, autonomous regions, and municipalities (except Tibet, Hong Kong, Macao, and Taiwan).

PARTICIPANTS

There were 213 795 Han school children between 7 and 18 years old enrolled in our study. All participants were sampled by stratified cluster.

PRIMARY AND SECONDARY OUTCOME MEASURES

Short stature; Chinese and WHO age-specific and gender-specific height growth references were used for short stature assessment.

RESULTS

The age-standardised and age-gender-standardised prevalence of short stature nationwide was 3.70% and 2.69% according to Chinese and WHO growth references, respectively. The short stature prevalence differed significantly among age groups, urban and rural areas, and regions with different socioeconomic development levels (all p<0.0001). The prevalence was 2.23% in urban versus 5.12% in rural areas (p<0.001). The prevalence was 2.60% in developed, 3.72% in intermediately developed, and 4.69% in underdeveloped regions (p<0.0001). These values were all according to China's growth reference, but similar patterns were observed on prevalence based on the WHO reference. The spatial distribution of prevalence of short stature presented a clustered pattern. Moran's I value was 0.474 (p<0.001) and 0.478 (p<0.001) according to the Chinese and WHO growth references, respectively. The southwest part of China showed a higher prevalence of short stature, whereas lower prevalence of short stature was observed mainly in the northeast part of China.

CONCLUSIONS

There is an appreciably high prevalence of short stature in rural, underdeveloped areas of China. There are high prevalence spatial clusters of short stature in southwestern China. This provides corroborating evidence for a tailored strategy on short stature prevention and reduction in special areas.

Identification and characterization of areas of high and low risk for asymptomatic malaria infections at sub-village level in Ratanakiri, Cambodia

BACKGROUND

Malaria elimination needs a concentration of activities towards identification of residual transmission foci and intensification of efforts to eliminate the last few infections, located in so-called 'malaria hotspots'. Previous work on characterizing malaria transmission hotspots has mainly focused on falciparum malaria and especially on symptomatic cases, while the malaria reservoir is expected to be mainly concentrated in the asymptomatic human population when transmission is low. For Plasmodium vivax, there has been less effort in identifying transmission hotspots. The main aim of this study was to uncover micro-epidemiological mechanisms of clustering of malaria infections at a sub-village level, based on geographical or behavioural features.

METHODS

A cross-sectional survey was performed in three villages within the highest malaria endemic province of Cambodia. The survey took place in the dry season, when the malaria reservoir is expected to be low and residing in the asymptomatic part of the population. Village and field locations of households were georeferenced, blood samples were taken from as many residents as possible and a short questionnaire probing for individual risk factors was taken. Asymptomatic malaria carriers were detected by PCR, and geographical clustering analysis (SaTScan) as well as risk factor analysis were performed.

RESULTS

A total of 1540 out of 1792 (86%) individuals were sampled. Plasmodial DNA was detected in 129 individuals (8.4%). P. vivax was most prevalent (5.5%) followed by Plasmodium malariae (2.1%) and Plasmodium falciparum (1.6%). Mixed infection occurred in 12 individuals. In two out of three villages geographical clustering of high and low malaria infection risk was clearly present. Cluster location and risk factors associated with the infection differed between the parasite species. Age was an important risk factor for the combined Plasmodium infections, while watching television at evenings was associated with increased odds of P. vivax infections [OR (CI): 1.86 (0.95-3.64)] and bed net use was associated with reduced odds of P. falciparum infections [OR (CI): 0.25 (0.077-0.80)].

CONCLUSIONS

Clusters of malaria carriers were malaria species specific and often located remotely, outside village centres. As such, at micro-epidemiological level, malaria is not a single disease. Further unravelling the micro-epidemiology of malaria can enable programme managers to define the interventions likely to contribute to halt transmission in a particular hotspot location.

Micro-epidemiology and spatial heterogeneity of P. vivax parasitaemia in riverine communities of the Peruvian Amazon: A multilevel analysis

Malaria has steadily increased in the Peruvian Amazon over the last five years. This study aimed to determine the parasite prevalence and micro-geographical heterogeneity of Plasmodium vivax parasitaemia in communities of the Peruvian Amazon. Four cross-sectional active case detection surveys were conducted between May and July 2015 in four riverine communities in Mazan district. Analysis of 2785 samples of 820 individuals nested within 154 households for Plasmodium parasitaemia was carried out using light microscopy and qPCR. The spatio-temporal distribution of Plasmodium parasitaemia, dominated by P. vivax, was shown to cluster at both household and community levels. Of enrolled individuals, 47% had at least one P. vivax parasitaemia and 10% P. falciparum, by qPCR, both of which were predominantly sub-microscopic and asymptomatic. Spatial analysis detected significant clustering in three communities. Our findings showed that communities at small-to-moderate spatial scales differed in P. vivax parasite prevalence, and multilevel Poisson regression models showed that such differences were influenced by factors such as age, education, and location of households within high-risk clusters, as well as factors linked to a local micro-geographic context, such as travel and occupation. Complex transmission patterns were found to be related to human mobility among communities in the same micro-basin.