Mining geographic variations of Plasmodium vivax for active surveillance: a case study in China

Shi, Benyun; Tan, Qinggui; Zhou, Xiao-Nong; Liu, Jiming

doi:10.1186/s12936-015-0719-y

Cited by 15 publications

(14 citation statements)

References 43 publications

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“…We defined N h as the total population in Xiangqiao district (Ns = 0.6 million). Some undetermined parameters (e.g., the initial values of S v , E v and I v , the transmission rate and growth rate of mosquitoes) were fitted by Markov chain Monte Carlo (MCMC) method [ 12 ]. Other parameters were referred to related studies [ 13 ].…”

Section: Methodsmentioning

confidence: 99%

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Early rigorous control interventions can largely reduce dengue outbreak magnitude: experience from Chaozhou, China

Liu

Zhu

et al. 2017

BMC Public Health

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BackgroundDengue fever is a severe public heath challenge in south China. A dengue outbreak was reported in Chaozhou city, China in 2015. Intensified interventions were implemented by the government to control the epidemic. However, it is still unknown the degree to which intensified control measures reduced the size of the epidemics, and when should such measures be initiated to reduce the risk of large dengue outbreaks developing?MethodsWe selected Xiangqiao district as study setting because the majority of the indigenous cases (90.6%) in Chaozhou city were from this district. The numbers of daily indigenous dengue cases in 2015 were collected through the national infectious diseases and vectors surveillance system, and daily Breteau Index (BI) data were reported by local public health department. We used a compartmental dynamic SEIR (Susceptible, Exposed, Infected and Removed) model to assess the effectiveness of control interventions, and evaluate the control effect of intervention timing on dengue epidemic.ResultsA total of 1250 indigenous dengue cases was reported from Xiangqiao district. The results of SEIR modeling using BI as an indicator of actual control interventions showed a total of 1255 dengue cases, which is close to the reported number (n = 1250). The size and duration of the outbreak were highly sensitive to the intensity and timing of interventions. The more rigorous and earlier the control interventions implemented, the more effective it yielded. Even if the interventions were initiated several weeks after the onset of the dengue outbreak, the interventions were shown to greatly impact the prevalence and duration of dengue outbreak.ConclusionsThis study suggests that early implementation of rigorous dengue interventions can effectively reduce the epidemic size and shorten the epidemic duration.

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Section: Methodsmentioning

confidence: 99%

“…Parameters were estimated by sampling the posterior distribution, using the Metropolis-Hasting MCMC algorithm [ 12 ]. Nine chains with initial conditions were explored to examine the convergence of posterior distribution.…”

Section: Methodsmentioning

confidence: 99%

Early rigorous control interventions can largely reduce dengue outbreak magnitude: experience from Chaozhou, China

Liu

Zhu

et al. 2017

BMC Public Health

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“…The procedure of the MCMC method is carried out as follows [ 39 ]: First, we initialize all of the independent model parameters K and a , each of which follows a normal distribution. We then generate the value of the modeling cases based on new parameters for calculating the posteriori likelihood P ( K *, a *|Γ) according to Eq (11) .…”

Section: Methodsmentioning

confidence: 99%

“…Third, human mobility as a spatio-temporal driver of dengue spreading dynamics [ 36 ], is estimated based on the radiation model proposed by Simini et al [ 38 ]. Underlying transmission parameters are quantified by fitting the model to real-world observations using machine learning methods, such as the Markov chain Monte Carlo (MCMC) method [ 39 ]. The issue of incomplete surveillance data is addressed by comparing the estimated incidence rates and surveillance data with a reported rate.…”

Section: Introductionmentioning

confidence: 99%

Inferring the Spatio-temporal Patterns of Dengue Transmission from Surveillance Data in Guangzhou, China

et al. 2016

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BackgroundDengue is a serious vector-borne disease, and incidence rates have significantly increased during the past few years, particularly in 2014 in Guangzhou. The current situation is more complicated, due to various factors such as climate warming, urbanization, population increase, and human mobility. The purpose of this study is to detect dengue transmission patterns and identify the disease dispersion dynamics in Guangzhou, China.MethodologyWe conducted surveys in 12 districts of Guangzhou, and collected daily data of Breteau index (BI) and reported cases between September and November 2014 from the public health authority reports. Based on the available data and the Ross-Macdonald theory, we propose a dengue transmission model that systematically integrates entomologic, demographic, and environmental information. In this model, we use (1) BI data and geographic variables to evaluate the spatial heterogeneities of Aedes mosquitoes, (2) a radiation model to simulate the daily mobility of humans, and (3) a Markov chain Monte Carlo (MCMC) method to estimate the model parameters.Results/ConclusionsBy implementing our proposed model, we can (1) estimate the incidence rates of dengue, and trace the infection time and locations, (2) assess risk factors and evaluate the infection threat in a city, and (3) evaluate the primary diffusion process in different districts. From the results, we can see that dengue infections exhibited a spatial and temporal variation during 2014 in Guangzhou. We find that urbanization, vector activities, and human behavior play significant roles in shaping the dengue outbreak and the patterns of its spread. This study offers useful information on dengue dynamics, which can help policy makers improve control and prevention measures.

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“…Different from the COVID-19, malaria is a mosquito-borne infectious disease, whose transmission depends on various impact factors, such as climate [28,29], human movement [30][31][32][33], and socio-economic factors [34,35]. In this study, we adopt the notion of vectorial capacity to represent the transmission potential of a mosquito population in the absence of Plasmodium.…”

Section: Discussionmentioning

confidence: 99%

Accessing the Syndemic of COVID-19 and Malaria Intervention in Africa

Shi

Zheng²,

Shang³

et al. 2020

Preprint

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Background: The COVID-19 pandemic has caused substantial disruptions to health services in the low and middle-income countries with a high burden of other diseases, such as malaria in sub-Saharan Africa. As the COVID-19 pandemic spread to Africa, there is an urgent need to assess the impact of COVID-19 pandemic on malaria transmission potential in malaria-endemic countries in Africa.Methods: We present a data-driven method to quantify the extent to which the COVID-19 pandemic, as well as various non-pharmaceutical interventions (NPIs), could lead to the change of malaria transmission potential in 2020. First, we adopt a particle Markov Chain Monte Carlo method to estimate epidemiological parameters in each country by fitting the time series of the cumulative number of COVID-19 cases. Then, we simulate the epidemic dynamics of COVID-19 under two groups of NPIs: (i) contact restriction and social distancing, and (ii) early identification and isolation of cases. Based on the simulated epidemic curves, we quantify the impact of COVID-19 epidemic and NPIs on the distribution of insecticide-treated nets (ITNs). Finally, by treating the total number of ITNs available in each country in 2020, we evaluate the negative effects of COVID-19 pandemic on malaria transmission potential based on the notion of vectorial capacity.Results: We conduct case studies in four malaria-endemic countries, Ethiopia, Nigeria, Tanzania, and Zambia, in Africa. The epidemiological parameters (i.e., the basic reproduction number R0 and the duration of infection DI ) of COVID-19 in each country are estimated as follows: Ethiopia (R0 = 1:57, DI = 5:32), Nigeria (R0 = 2:18, DI = 6:58), Tanzania (R0 = 2:47, DI = 6:01), and Zambia (R0 = 2:12, DI = 6:96). Based on the estimated epidemiological parameters, the epidemic curves simulated under various NPIs indicated that the earlier the interventions are implemented, the better the epidemic is controlled. Moreover, the effect of combined NPIs is better than contact restriction and social distancing only. By treating the total number of ITNs available in each country in 2020 as a baseline, our results show that even with stringent NPIs, malaria transmission potential will remain higher than expected in the second half of 2020.Conclusions: By quantifying the impact of various NPI response to the COVID-19 pandemic on malaria transmission potential, this study provides a way to jointly address the syndemic between COVID-19 and malaria in malaria-endemic countries in Africa. The results suggest that the early intervention of COVID-19 can effectively reduce the scale of the epidemic and mitigate its impact on malaria transmission potential.

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Mining geographic variations of Plasmodium vivax for active surveillance: a case study in China

Cited by 15 publications

References 43 publications

Early rigorous control interventions can largely reduce dengue outbreak magnitude: experience from Chaozhou, China

Early rigorous control interventions can largely reduce dengue outbreak magnitude: experience from Chaozhou, China

Inferring the Spatio-temporal Patterns of Dengue Transmission from Surveillance Data in Guangzhou, China

Accessing the Syndemic of COVID-19 and Malaria Intervention in Africa

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