BackgroundMalaria remains a public health concern in Hubei Province despite the significant decrease in malaria incidence over the past decades. Furthermore, history reveals that malaria transmission is unstable and prone to local outbreaks in Hubei Province. Thus, understanding spatial, temporal, and spatiotemporal distribution of malaria is needed for the effective control and elimination of this disease in Hubei Province.MethodsAnnual malaria incidence at the county level was calculated using the malaria cases reported from 2004 to 2011 in Hubei Province. Geographical information system (GIS) and spatial scan statistic method were used to identify spatial clusters of malaria cases at the county level. Pure retrospective temporal analysis scanning was performed to detect the temporal clusters of malaria cases with high rates using the discrete Poisson model. The space-time cluster was detected with high rates through the retrospective space-time analysis scanning using the discrete Poisson model.ResultsThe overall malaria incidence decreased to a low level from 2004 to 2011. The purely spatial cluster of malaria cases from 2004 to 2011 showed that the disease was not randomly distributed in the study area. A total of 11 high-risk counties were determined through Local Moran’s I analysis from 2004 to 2011. The method of spatial scan statistics identified different 11 significant spatial clusters between 2004 and 2011. The space-time clustering analysis determined that the most likely cluster included 13 counties, and the time frame was from April 2004 to November 2007.ConclusionsThe GIS application and scan statistical technique can provide means to detect spatial, temporal, and spatiotemporal distribution of malaria, as well as to identify malaria high-risk areas. This study could be helpful in prioritizing resource assignment in high-risk areas for future malaria control and elimination.
BackgroundHubei Province, China, has been operating a malaria elimination programme. This study aimed at investigating the epidemiologic characteristics of malaria in Hubei Province (2005–2016) to plan resource allocation for malaria elimination.MethodsData on all malaria cases from 2005 to 2016 in all counties of Hubei Province were extracted from a web-based reporting system. The numbers of indigenous and imported cases during the disease control (2005–2010) and elimination (2011–2016) stages, as well as their spatiotemporal distribution, were compared.ResultsA total of 8109 malaria cases were reported from 2005 to 2016 (7270 and 839 cases during the control and elimination stages, respectively). Between 2005 and 2010, indigenous malaria cases comprised the majority of total cases (7114/7270; 97.9%), and Plasmodium vivax malaria cases accounted for most malaria cases (5572/7270; 76.6%). No indigenous malaria cases have been reported in Hubei Province since 2013. Imported malaria cases showed a gradually increasing trend from 2011 to 2016, Plasmodium falciparum was the predominant species in these cases, and the number of counties with imported cases increased from 4 in 2005 to 47 in 2016. During the control and elimination stages, the most likely spatial clusters for indigenous cases included 13 and 11 counties, respectively. However, the cluster of indigenous malaria cases has not been identified since September 2011. For imported cases, the most likely cluster and three secondary clusters during both stages were identified.ConclusionsHubei Province has made significant achievements in controlling and eliminating malaria; however, the region now faces some challenges associated with the increasing number and distribution of imported malaria cases. Priorities for malaria elimination should include better management of imported malaria cases, prevention of secondary malaria transmission, and ensuring the sustainability of malaria surveillance.
Background: There have been an increasing number of imported cases of malaria in Hubei Province in recent years. In particular, the number of cases of Plasmodium ovale spp. and Plasmodium malariae significantly increased, which resulted in increased risks during the malaria elimination phase. The purpose of this study was to acquire a better understanding of the epidemiological characteristics of P. ovale spp. and P. malariae imported to Hubei Province, China, so as to improve case management. Methods: Data on all malaria cases from January 2014 to December 2018 in Hubei Province were extracted from the China national diseases surveillance information system (CNDSIS). This descriptive study was conducted to analyse the prevalence trends, latency periods, interval from onset of illness to diagnosis, and misdiagnosis of cases of P. ovale spp. and P. malariae malaria. Results: During this period, 634 imported malaria cases were reported, of which 87 P. ovale spp. (61 P. ovale curtisi and 26 P. ovale wallikeri) and 18 P. malariae cases were confirmed. The latency periods of P. ovale spp., P. malariae, Plasmodium vivax, and Plasmodium falciparum differed significantly, whereas those of P. ovale curtisi and P. ovale wallikeri were no significant difference. The proportion of correct diagnosis of P. ovale spp. and P. malariae malaria cases were 48.3% and 44.4%, respectively, in the hospital or lower-level Centers for Disease Control and Prevention (CDC). In the Provincial Reference Laboratory, the sensitivity of microscopy and rapid diagnostic tests was 94.3% and 70.1%, respectively, for detecting P. ovale spp., and 88.9% and 38.9%, respectively, for detecting P. malariae. Overall, 97.7% (85/87) of P. ovale spp. cases and 94.4% (17/18) of P. malariae cases originated from Africa. Conclusion: The increase in the number of imported P. ovale spp. and P. malariae cases, long latency periods, and misdiagnosis pose a challenge to this region. Therefore, more attention should be paid to surveillance of imported cases of P. ovale spp. and P. malariae infection to reduce the burden of public health and potential risk of malaria.
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