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Background: Anhui Province is currently facing an increase in imported malaria cases as a result of globalization and international travel. In response, Anhui Province has implemented a comprehensive adaptive framework to effectively address this threat. Methods: This study collected surveillance data from 2012 to 2022 in Anhui Province. Descriptive statistics were used to analyze the epidemiological characteristics of imported malaria cases. Additionally, multivariate logistic regression was employed to identify factors associated with severe malaria. Documents were reviewed to document the evolution of the adaptive framework designed to combat imported malaria. The effectiveness of the adaptive framework was evaluated based on the rates of timely medical visits, timely diagnosis, and species identification. Results: During the study period, a total of 1008 imported malaria cases were reported across 77 out of 105 counties in Anhui Province, representing a coverage of 73.33%. It was found that 10.52% of imported cases went undiagnosed for more than seven days after onset. The multivariate analysis revealed several potential risk factors for severe malaria, including increasing age (OR = 1.049, 95%CI:1.015–1.083), occupation (waitperson vs. worker, OR = 2.698, 95%CI:1.054–6.906), a longer time interval between onset and the initial medical visit (OR = 1.061, 95%CI:1.011–1.114), and misdiagnosis during the first medical visit (OR = 5.167, 95%CI:2.535–10.533). Following the implementation of the adaptive framework, the rates of timely medical visits, timely diagnosis, and species identification reached 100.00%, 78.57%, and 100.00%, respectively. Conclusions: Anhui Province has successfully developed and implemented an adaptive framework for addressing imported malaria, focusing on robust surveillance, prompt diagnosis, and standardized treatment. The experiences gained from this initiative can serve as a valuable reference for other non-endemic areas. [ABSTRACT FROM AUTHOR]

Background: The area of Oncomelania hupensis snail remains around 3.6 billion m2, with newly emerging and reemergent habitats continuing to appear in recent years. This study aimed to explore the long-term dynamics of snail density before and after the operation of Three Gorges Dam (TGD). Methods: Data of snail survey between 1990 and 2019 were collected from electronic databases and national schistosomiasis surveillance. Meta-analysis was conducted to estimate the snail density. Joinpoint model was used to identify the changing trend and inflection point. Inverse distance weighted interpolation (IDW) was used to determine the spatial distribution of recent snail density. Results: A total of 3777 snail survey sites with a precise location of village or beach were identified. For the downstream area, snail density peaked in 1998 (1.635/0.11 m2, 95% CI: 1.220, 2.189) and fluctuated at a relatively high level before 2003, then declined steadily from 2003 to 2012. Snail density maintained lower than 0.150/0.11 m2 between 2012 and 2019. Joinpoint model identified the inflection of 2003, and a significant decreasing trend from 2003 to 2012 with an annual percentage change (APC) being − 20.56% (95% CI: − 24.15, − 16.80). For the upstream area, snail density peaked in 2005 (0.760/0.11 m2, 95% CI: 0.479, 1.207) and was generally greater than 0.300/0.11 m2 before 2005. Snail density was generally lower than 0.150/0.11 m2 after 2011. Snail density showed a significant decreasing trend from 1990 to 2019 with an APC being − 6.05% (95% CI: − 7.97, − 7.09), and no inflection was identified. IDW showed the areas with a high snail density existed in Poyang Lake, Dongting Lake, Jianghan Plain, and the Anhui branch of the Yangtze River between 2015 and 2019. Conclusions: Snail density exhibited a fluctuating downward trend in the Yangtze River basin. In the downstream area, the operation of TGD accelerated the decline of snail density during the first decade period, then snail density fluctuated at a relatively low level. There still exists local areas with a high snail density. Long-term control and monitoring of snails need to be insisted on and strengthened. [ABSTRACT FROM AUTHOR]

Background: Although autochthonous malaria cases are no longer reported in Anhui Province, China, imported malaria has become a major health concern. The proportion of reported malaria cases caused by Plasmodium ovale spp. increased to levels higher than expected during 2012 to 2019, and showed two peaks, 19.69% in 2015 and 19.35% in 2018. Methods: A case-based retrospective study was performed using data collected from the China Information System for Disease Control and Prevention (CISDCP) and Information System for Parasitic Disease Control and Prevention (ISPDCP) from 2012 to 2019 to assess the trends and differences between Plasmodium ovale curtisi (P. o. curtisi) and Plasmodium ovale wallikeri (P. o. wallikeri). Epidemiological characteristics were analyzed using descriptive statistics. Results: Plasmodium o. curtisi and P. o. wallikeri were found to simultaneously circulate in 14 African countries. Among 128 patients infected with P. ovale spp., the proportion of co-infection cases was 10.16%. Six cases of co-infection with P. ovale spp. and P. falciparum were noted, each presenting with two clinical attacks (the first attack was due to P. falciparum and the second was due to P. ovale spp.) at different intervals. Accurate identification of the infecting species was achieved among only 20.00% of cases of P. ovale spp. infection. At the reporting units, 32.17% and 6.96% of cases of P. ovale spp. infection were misdiagnosed as P. vivax and P. falciparum infections, respectively. Conclusion: The present results indicate that the potential of P. ovale spp. to co-infect with other Plasmodium species has been previously underestimated, as is the incidence of P. ovale spp. in countries where malaria is endemic. P. o. curtisi may have a long latency period of > 3 years and potentially cause residual foci, thus posing challenges to the elimination of malaria in P. ovale spp.-endemic areas. Considering the low rate of species identification, more sensitive point-of-care detection methods need to be developed for P. ovale spp. and introduced in non-endemic areas. [ABSTRACT FROM AUTHOR]

• The combined toolbox (Wondfo RDTs plus microscopy) improved the surveillance system sensitivity for malaria in Anhui province. • The improvement was mainly attributed to the excellent ability of RDTs to detect P. falciparum infections. On the other hand, microscopy compensates for some limitations of the use of RDTs in field practice. • Using more than one diagnostic tool to strengthen the surveillance system was effective in the post-elimination stage. Background: In the Anhui Province, China, efforts to interrupt the local malaria transmission were successful, with no endemic cases reported since 2014. Contrastingly, imported malaria cases are still being reported, indicating a disease reintroduction risk after years of elimination. A good surveillance system is key for avoiding the risk, detecting imported cases and possible cases associated with local transmission early. Therefore, rapid diagnostic tests (RDTs) were combined with microscopy to strengthen malaria surveillance in the province. Herein, we aimed to evaluate the efficacy of this surveillance strategy. Methods: We conducted a retrospective study using malaria surveillance data from January 2016 to June 2020. Epidemiological characteristics and diagnostic information were analysed using descriptive and comparative statistics. The diagnostic performance of the combined toolbox (Wondfo RDTs plus microscopy) was evaluated based on its sensitivity, specificity, positive and negative predictive values, and Cohen's kappa coefficient, using real-time polymerase chain reaction as the gold standard. Results: The combined toolbox displayed a higher overall sensitivity for malaria cases than that of microscopy alone (93.74% vs 89.37%; p adj <0.05), which could detect 94.65%, 88.16%, 95.00%, and 100.00% of Plasmodium falciparum, P. ovale, P. vivax , and P. malariae infections, respectively. In clinical practice, Wondfo RDTs ability to detect P. falciparum infections was better than that of microscopy (97.55% vs 89.67%, p adj < 0.05). In contrast, microscopy displayed a higher specificity than that of Wondfo RDTs (81.82% vs 63.28%, p adj <0.05). Moreover, the consistency between microscopy and the gold standard results was also better than that of RDTs (Kappa value:0.669 vs 0.596). Conclusions: The combination of microscopy and RDTs is an effective strategy for malaria surveillance because it possibly detected more P. falciparum infections due to the introduction of RDTs. In contrast, microscopy is complementary to some limitations related to the use of RDTs in field practice. Thus, monitoring malaria cases in non-endemic areas may require employing more than one diagnostic tool in surveillance strategies. Moreover, further understanding of the advantages and disadvantages of different detection methods is necessary for applying optimum combinations in field settings. [ABSTRACT FROM AUTHOR]